If you’ve been paying attention to Austin’s job market, you’ve probably noticed something shifting beneath the surface of all the usual tech headlines. Sure, Amazon, Apple, and Google are still hiring. But the real story? It’s about an economy that’s finally learning to diversify.
We just analyzed 67,477 available job postings across Austin in January 2026, and the data tells a fascinating story about where opportunity really lives right now—whether you’re a software engineer, a nurse, or someone trying to figure out your next move.
Let’s start with what everyone expects: tech is still the heavyweight in Austin. Major corporations like Amazon, IBM, Apple, and Google continue to lead hiring, and our startup ecosystem has 1,100+ open positions actively recruiting. That’s not changing anytime soon.
But here’s the thing—tech employment growth is actually slowing relative to other sectors. Management, sales, and computer/mathematical occupations still dominate the top job postings, but they’re not expanding at the rates we saw five years ago. Meanwhile, healthcare and education are growing at 5.7% and creating real momentum.
Southwest Airlines is bringing 2,000 jobs to Austin. Nvidia added 650 positions. Compal announced 1,000 new roles. These aren’t just tech jobs—they’re diversified positions across operations, logistics, manufacturing, and support functions.
Here’s what surprised us most in the data: healthcare and education posted 9,027 combined openings, and this sector is expanding faster than tech right now. Education and health services grew 5.7% year-over-year, adding 8,900 jobs. That’s real, sustained growth.
Why does this matter? Because if you’re not a coder or engineer, this is the segment where serious opportunity is hiding. Top nursing positions are earning $31,000+ above our city average of $71,356. HCA Healthcare and UT Austin are among the largest hiring entities in the metro. And certification pathways in healthcare are clearer and faster than they’ve ever been.
The barrier to entry is also lower than tech in many cases. While 94% of tech occupations require a bachelor’s degree or higher, healthcare offers pathways for certification-focused roles that pay competitive salaries without the four-year commitment.
Let’s talk money, because that’s what really drives career decisions.
Austin’s average salary sits at $87,000 citywide—well above national averages. But the distribution is fascinating. Vice Presidents are commanding $158,116. Software engineers across Tesla, Dell, and IBM are pulling premium compensation. But sales associates are earning $61,000-$74,000, and that doesn’t require a PhD.
Here’s a practical breakdown:
The pattern is clear: if you can develop sales skills or move into nursing/healthcare management, Austin rewards you generously.
Austin’s top three in-demand skills across all sectors are communication, customer service, and management. Not “AI expertise.” Not “blockchain proficiency.” Just the fundamentals.
For healthcare, certifications dominate. For tech, bachelor’s degrees are table stakes. But for most mid-level positions? Communication and the ability to manage people or relationships are what distinguish candidates.
This is actually liberating if you think about it. You don’t need to chase every new technology trend to stay relevant. You need to get genuinely good at talking to people, solving their problems, and eventually leading others through that process.
Austin’s unemployment remains consistently below the national average. Our region added 718,700 jobs since 2004—ranking first among large metros for job creation. In 2025 alone, we added 14,133 jobs. Regional GDP hit $268 billion in 2024, growing 3.7% in real GDP year-over-year.
Finance, construction, and green energy sectors are all experiencing significant expansion. These aren’t one-off spikes—they’re structural shifts in how Austin’s economy is organizing itself.
If you’re job hunting or thinking about your next move in 2026, here’s what actually matters:
If you’re in tech: You’re still in a strong position, but you might face more competition. Your salary power is real, but growth rates are moderating. Consider whether adjacent roles (product management, technical sales, operations) might give you better leverage.
If you’re in healthcare: This is your moment. Growth is real, compensation is rising, and Austin’s population expansion means sustained demand. Certification programs are a legitimate fast-track to $70,000+ positions.
If you’re in sales, management, or operations: Austin is actively hiring across all three. These roles pay surprisingly well—$61,000-$74,000 for sales associates—and advancement into management (where $158,116 VP salaries live) is achievable.
If you’re transitioning careers: Austin’s demand for communication, customer service, and management skills means you don’t need to start from zero. Your experience in one sector can translate to another.
Austin’s job market in 2026 isn’t “tech or nothing.” It’s diversified, growing, and full of paths to solid six-figure compensation if you develop the right skills and experience. The tech sector remains dominant, but healthcare, finance, and operations are the real growth engines.
The best time to move intentionally into one of these growing sectors? That’s right now, while demand is still outpacing supply.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>Let’s be real: if you’re job hunting in 2026 and you’re not thinking strategically about AI, you’re already behind.
I’m not talking about letting ChatGPT write your cover letter (please don’t). I’m talking about understanding how AI is fundamentally reshaping how companies find, filter, and evaluate candidates—and then using that knowledge to your advantage.
97% of Fortune 500 companies now use AI-powered ATS systems to screen resumes — and mid-market adoption is catching up fast. Hiring managers actively want to know how you use AI tools. LinkedIn is becoming an SEO game where optimization matters as much as your actual experience. The job market has shifted, and the candidates winning right now are the ones who’ve adapted.
Here’s your playbook.
Let’s start with the uncomfortable truth: before a human ever sees your resume, an AI system is deciding whether you’re worth their time.
These aren’t your grandmother’s keyword-matching bots. Modern ATS platforms use semantic analysis to understand meaning and context. They’re looking for evidence that you can do the job—not just that you’ve written the exact job title somewhere in your document.
But here’s the problem: a significant portion of resumes never make it to a human’s eyes — not because of weak experience, but because the ATS can’t parse the file due to formatting issues.
So step one is technical:
Here’s where a lot of job seekers mess up: they let AI write their resume from scratch. Then they wonder why it feels generic and doesn’t actually represent who they are.
Flip the script.
Start with your real experience. Write out what you actually did, the results you created, the problems you solved. This is your authentic foundation—it has to be true.
Then use AI as an editor. Ask it to polish your language, optimize for ATS keywords without losing your voice, tighten bullet points, and ensure you’re highlighting impact (numbers, outcomes, concrete results).
This approach gives you the best of both worlds: authenticity that resonates with humans, optimization that gets past the robots, and a resume that actually represents you.
Here’s a stat that should change how you think about LinkedIn: 6 people get hired through LinkedIn every minute. That’s 8,600 people daily.
But getting hired on LinkedIn doesn’t start with hoping a recruiter stumbles on your profile. It starts with SEO optimization.
Your LinkedIn summary isn’t just a place to tell your story anymore—it’s a searchable database. Recruiters use specific keywords when they’re sourcing candidates, and if your profile isn’t optimized for those keywords, you won’t show up in their search results.
Optimize your headline and summary for:
You’re not being dishonest; you’re making sure you’re discoverable to the right people. LinkedIn job postings get an average of 10 applications in the first 24 hours. Being findable is half the battle.
In 2026, interviewers aren’t just evaluating whether you can do your job. They’re asking: “Do you understand how AI tools work, and can you use them strategically?”
This is a test of adaptability and sophistication.
The right answer isn’t “I use ChatGPT every day.” It’s more nuanced.
Talk about specific tools you’ve used (AI-powered analytics platforms, collaboration tools with AI features, content optimization software) and explain how they’ve made you more effective. Show that you understand the limitations too—you’re not blindly trusting AI, you’re evaluating it critically and using it as a tool, not a replacement.
The wrong answer? “I haven’t really used AI much” or “I’m waiting to see what happens with it.” That signals you’re not paying attention to the market you’re trying to work in.
Familiarity with AI collaboration and analytical tools can genuinely set your profile apart. Not because you’re an expert—but because you’re aware and you’re adapting.
Here’s where a lot of talented people leave thousands on the table.
Most hiring managers expect you to negotiate salary. Yet a surprisingly large share of professionals never do.
Candidates who negotiate consistently earn more than those who accept the first offer — often meaningfully so. Some secure increases well into five figures on base salary alone.
Let that sink in. You could be setting the tone for your entire tenure at a company by negotiating (professionally and respectfully) from the beginning.
The good news? Pay transparency laws now operate in 16 states plus Washington D.C. That means you have more leverage and more information than ever before. Use it.
Negotiation isn’t aggressive. It’s professional. Do it.
Here’s what’s changed in 2026: hiring managers care less about what you used to do and more about what you can do now.
This is huge.
You don’t need a completely new resume for every job. You need to reposition your existing experience to fit where you’re going next.
If you’ve managed projects, emphasize the strategic thinking and problem-solving. If you’ve led teams, highlight how you’ve navigated change. If you’ve worked across departments, frame it as cross-functional collaboration and communication.
Your experience is real. How you package it for the next chapter should be intentional.
Competition is real. Applications are up, processes are more competitive, and AI has raised the bar for what “prepared” looks like.
But the people winning aren’t necessarily more talented than everyone else. They’re the ones who’ve understood that the job search playbook has changed. They’re treating their job search like a strategic project. They’re optimizing where it matters (ATS, LinkedIn, salary negotiation) while staying authentic where it counts (your real experience, your voice, your values).
AI isn’t the threat to your career. Being unprepared for how AI is reshaping hiring is.
Now go build the job search you actually deserve.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>Austin’s tech sector remains the city’s largest employer despite a wave of restructuring. Giants like Apple, Dell, AMD, Amazon, Google, Samsung, NVIDIA, and Arm all maintain significant Austin operations. The shift in 2026 is toward AI infrastructure and semiconductor roles rather than generalist software positions. NXP Semiconductors is exploring a major expansion of its Central Texas operations, and Arm — whose Austin engineers average $198K — continues to recruit. Google has committed to a $9.5B U.S. campus investment with over 10,000 jobs targeted for the broader market. That said, hiring is increasingly selective, with companies trading headcount for automation capability.
Healthcare is the single most recession-resistant hiring sector in Austin in 2026. Population growth continues to drive demand for clinical staff at every level. The most in-demand roles include registered nurses, physical therapists, respiratory therapists, occupational therapists, speech-language therapists, clinical social workers, and licensed professional counselors. Nomi Health’s regional office expansion in Austin is emblematic of the broader direct-care movement entering the market.
Austin’s sustained population inflow continues to fuel construction demand. With 558+ active new home communities in the metro area, construction hiring remains robust across trades, project management, and civil engineering. Infrastructure spending tied to corporate relocations and campus buildouts adds further momentum. Construction job gains (particularly outside the housing sector) are viewed as a leading indicator for continued hiring growth.
Financial services are a fast-growing segment. Frost Bank is doubling its Austin-area financial centers by 2026, adding 170 jobs. Sendero Wealth Management opened its first Austin office in 2026. Black Ore, an AI-driven tax technology firm, has established operations in Austin, blending fintech with traditional accounting roles.
Clean energy and startup activity round out Austin’s hiring landscape. The region’s startup ecosystem continues to attract venture capital, and remote-friendly roles in creative, entertainment, and hospitality sectors are also expanding alongside the city’s growing cultural footprint.
| Category | Hot Roles | |—|—| | Technology | Software Engineer, AI/ML Engineer, Cloud Infrastructure Engineer, Data Scientist, DevOps Engineer, Semiconductor Design Engineer | | Healthcare | Registered Nurse, Physical Therapist, Respiratory Therapist, Occupational Therapist, Speech-Language Pathologist, Clinical Social Worker | | Finance | Financial Analyst, Accountant, Wealth Manager, Tax Specialist | | Sales & Business | Account Executive, Sales Associate, Business Development Representative | | Construction | Project Manager, Civil Engineer, Skilled Trades Workers |
Austin wages are above the national average and, notably, accelerating — a finding confirmed by PNC’s March 2026 Regional Economics Analysis, which noted that average wage growth in Austin outpaced national and statewide trends through 2025. This is helping sustain consumer spending even as near-term job creation slows slightly.
| Metric | Figure |
|---|---|
| Median salary (Austin) | ~$71,181/year ($34.22/hr) — ZipRecruiter, Feb 2026 |
| Median salary (Playroll estimate) | ~$73,500/year |
| Median salary (Gusto) | $65,250/year |
| Average salary (PayScale) | ~$86,000/year |
| 80th percentile salary band | $60,000–$100,000 |
| Cost of living vs. national avg. | ~4% higher |
| Wage growth (Q4 2024) | +1.6% (PayScale) |
Austin’s wage acceleration is a double-edged dynamic: it supports workers and local consumer spending, but it is also one reason some companies are selectively reducing headcount or relocating certain roles to lower-cost Texas cities.
Austin’s labor market is selectively strong. The layoffs are concentrated in large legacy tech firms restructuring around AI, while expansion is driven by financial services, semiconductor, healthcare, and AI-native companies. The overall trajectory is positive but more measured than the hyper-growth years of 2021–2022.
Generated by Austin Hiring Trends Research Agent
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles for companies with high standards and specific needs. Schedule a call to discuss your search.
]]>Except the process took five weeks to get to an offer. By the time it arrived, he’d already accepted somewhere else. A company that moved in twelve days.
This story isn’t unusual. It happens every week. And the frustrating part is that it’s almost always preventable.
Based on our placement data over the past 18 months, here’s what we’re seeing in the Austin market:
The math doesn’t work. If your process is designed for a five-week timeline and the talent you want disappears in two weeks, your process is the problem.
We regularly see processes with five, six, or seven interview rounds. Panel interview. Technical assessment. Case study. Culture fit interview. Skip-level interview. Founder interview. Board member coffee chat.
Each round adds days to the timeline and increases the risk of candidate drop-off. The best hiring teams we work with cap their process at three to four rounds total, and they schedule them within a compressed window — ideally five to seven business days from first screen to final interview.
“We loved the candidate, but we need to check with [person who wasn’t in the interview].” This is a process design failure. Every person who has a vote on the hire should be part of the interview loop. If a stakeholder can veto the decision but isn’t included in the process, you’ve built in a structural delay.
Define your decision-makers upfront. Get them scheduled before the first interview, not after the last one.
The silence between interview rounds is where you lose people. A candidate has a great second interview on Tuesday. They hear nothing for eight days. During those eight days, another company has moved them through two rounds and extended an offer.
Simple fix: set an internal SLA for candidate communication. Every candidate hears from you within 48 hours of any interview, even if the update is “we’re still in process.” Silence communicates disinterest, and candidates interpret it exactly that way.
Nothing wastes more time than running a candidate through four rounds of interviews and then discovering you’re $40K apart on compensation. Have the compensation conversation early — ideally in the first recruiter screen. Confirm the range, confirm the candidate’s expectations, and make sure there’s alignment before investing everyone’s time.
This isn’t about anchoring or negotiation tactics. It’s about respecting the candidate’s time and your own.
This one is more philosophical, but it’s real. Some hiring managers hold out for a unicorn candidate who checks every single box — and in the process, they pass on excellent candidates who check 85% of the boxes and could be transformative in the role.
Perfection is the enemy of great hiring. If a candidate can do the job, grow in the role, and add value to your team, move on them. The mythical perfect candidate is either not available or not as perfect as you think.
The hiring teams with the highest close rates in our experience share these characteristics:
They pre-build the process before opening the role. Interview panels are scheduled, scorecards are defined, compensation ranges are approved, and decision timelines are set — all before the first resume arrives.
They move in parallel, not sequentially. Instead of waiting for one interviewer’s feedback before scheduling the next round, they run multiple interviews in the same week.
They designate a process owner. One person — usually the recruiter or hiring manager — is accountable for keeping the process on timeline. They have the authority to escalate delays and hold stakeholders accountable.
They treat the candidate experience as a product. Every touchpoint is intentional. Communication is prompt, professional, and personal. Logistics are handled smoothly. The candidate should leave the process — even if they don’t get the offer — thinking, “That was a well-run organization.”
Your hiring process is a reflection of your company. If it’s slow, disorganized, and uncommunicative, candidates will assume your company operates the same way. And in a market where top talent has options, they’ll choose the company that demonstrated competence and respect throughout the process.
Speed isn’t about cutting corners. It’s about removing unnecessary friction and showing candidates that you value their time as much as your own.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>If that sounds abstract, stay with me. The implications for recruiting are more concrete than you’d expect.
Moltbook is a platform where AI agents — the autonomous tools that increasingly act on behalf of professionals — can access structured information about companies: their culture, their tech stack, their hiring processes, their values, and their reputation. Think of it as a Glassdoor built for AI consumption rather than human browsing.
The premise is straightforward: as more professionals delegate research and decision-making tasks to AI agents, those agents need reliable, structured data sources to work from. Moltbook provides that layer.
An AI agent helping a candidate evaluate job opportunities might query Moltbook for information about a company’s engineering culture, work-life balance reputation, compensation benchmarks, and interview process. The company’s Moltbook presence directly influences what the agent reports back to the candidate.
Moltbook is one manifestation of a broader trend we’re calling the agent economy — an emerging ecosystem where AI agents transact, exchange information, and make decisions on behalf of humans and organizations.
This isn’t theoretical. Today, AI agents are already:
Each of these activities creates an information marketplace where the quality and accessibility of your company’s data directly affects your ability to attract talent. If your company’s public information is scattered, inconsistent, or hard for AI systems to parse, you’re already at a disadvantage — even if you don’t realize it yet.
Traditional employer branding focuses on human-readable content: career pages, social media posts, employee testimonials, blog articles. That content is still important. But it’s no longer sufficient.
In an agent-mediated world, your employer brand also needs to be machine-readable. That means:
Structured data about your company. Job descriptions, culture statements, benefits information, and team structures need to be available in formats that AI agents can parse reliably. Unstructured paragraphs on a career page are fine for humans but opaque to agents.
Consistency across platforms. AI agents aggregate information from multiple sources. If your LinkedIn page says one thing about company culture and your Glassdoor presence says another, the agent will surface that inconsistency — and it won’t favor the more flattering version.
Active presence on agent-native platforms. Early movers are establishing company profiles on Moltbook and similar platforms, ensuring that when an AI agent queries for information about their organization, the response is accurate, current, and compelling.
The companies and recruiting teams that are ahead of this curve share a few common strategies:
Appointing someone to own the agent-facing brand. This might sit in marketing, talent acquisition, or a new role entirely. The key is that someone is responsible for how the company appears to AI systems, not just human eyes.
Auditing their digital footprint for machine readability. This means reviewing job descriptions, career pages, and public information through the lens of AI consumption. Are the descriptions clear and structured? Are key facts (compensation ranges, benefits, tech stack, team sizes) explicitly stated rather than buried in paragraphs?
Creating structured content specifically for agent consumption. Some companies are publishing machine-readable FAQs, structured team profiles, and API-accessible company data that AI agents can query directly.
Monitoring agent sentiment. Just as companies track Glassdoor ratings and employer brand surveys, forward-thinking teams are starting to evaluate how AI agents characterize their organization. What does Claude say when asked about working at your company? What does a candidate’s agent report back? These outputs are becoming part of the brand equation.
The agent economy is early. Moltbook is young, the standards are evolving, and there’s legitimate debate about how fast this transition will happen. We’re not suggesting you need to overhaul your entire employer branding strategy tomorrow.
But we are suggesting you should be watching. The shift from human-mediated to agent-mediated talent discovery is happening, and the companies that build their presence now — while the platforms are small and the competition for attention is low — will have a structural advantage as adoption accelerates.
From our vantage point as recruiters, we see both sides of this equation. Candidates are increasingly using AI tools to evaluate opportunities. And companies that make it easy for those tools to find accurate, compelling information are getting more — and better — inbound interest.
The question isn’t whether AI agents will influence hiring decisions. They already do. The question is whether your company’s information ecosystem is ready for that reality.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>And it has real implications for how companies hire.
OpenClaw is a framework that lets you run AI agents locally — on your own hardware, without sending data to external APIs. The agents can interact with your file system, execute code, browse the web, manage workflows, and chain together complex multi-step tasks. All running on your laptop or your company’s on-prem servers.
This matters for three reasons:
Privacy. Enterprise data stays on enterprise hardware. No API calls to external providers means no data leaving the perimeter. For industries with strict compliance requirements — healthcare, finance, defense, legal — this is a game-changer.
Cost. Running models locally eliminates per-token API costs. For companies processing large volumes of data through AI, the savings are substantial once you amortize the hardware investment.
Control. Local agents can be customized, fine-tuned, and integrated deeply into existing workflows in ways that hosted API services can’t match. You own the full stack.
The shift toward local AI agents is already generating demand for skills and roles that barely existed a year ago. Here’s what we’re seeing:
These are engineers who specialize in building, deploying, and maintaining autonomous AI agents. Unlike traditional ML engineers who focus on model training, agent engineers focus on orchestration — how multiple AI components work together to accomplish complex tasks. They need to understand prompt engineering, tool use, memory management, and error handling in agentic systems.
This role is emerging fast, and the talent pool is thin. Companies that start recruiting for it now will have a significant head start.
Running AI models locally requires a different infrastructure stack than cloud-based deployments. You need engineers who understand GPU provisioning, model optimization (quantization, distillation), inference serving, and hardware-software co-optimization. These specialists sit at the intersection of ML engineering and systems engineering.
Local AI agents that interact with file systems, execute code, and access internal tools create new attack surfaces. AI security engineers specialize in sandboxing agent behavior, implementing access controls, auditing agent actions, and preventing prompt injection attacks. This is a nascent field, but the demand is already real — particularly in regulated industries.
As companies deploy more AI agents internally, someone needs to manage the portfolio: which agents are running, what they’re doing, how they’re performing, and when they need to be updated or retired. This is the emerging field of AI operations — part project management, part technical oversight, part governance.
If you’re a hiring leader, here’s how to think about the local AI agent trend:
Don’t wait for the job title to standardize. The roles I described above don’t have consistent titles yet. You might find the right person listed as a “Senior Software Engineer” or “DevOps Lead” or “ML Platform Engineer.” Look for the skills, not the title.
Open-source engagement is a signal. Candidates who’ve contributed to OpenClaw or similar projects — even if just in documentation, bug fixes, or community support — are demonstrating initiative and technical curiosity in a field that’s moving faster than any formal training program can keep up with.
Prioritize security thinking. Any candidate you hire to work on AI agents should be able to articulate security implications without prompting. If they can’t explain how an AI agent could be exploited or how to prevent unauthorized actions, they’re not ready for production deployment.
Consider the build-vs-buy dynamic. Local AI agents shift the calculus from “which AI vendor do we use?” to “what do we build ourselves?” That requires a different kind of talent — people who can architect systems, not just configure services.
OpenClaw’s explosive growth tells us something important: the AI landscape is decentralizing. The assumption that AI would remain concentrated in a few large providers is being challenged by open-source communities that move fast, iterate in public, and prioritize user control.
For hiring, this means the talent you need is evolving. The AI skills that were sufficient in 2024 — prompt engineering, API integration, basic model evaluation — are becoming table stakes. The next wave of AI talent will be defined by the ability to build, deploy, and manage autonomous systems that run inside the enterprise.
The companies that recognize this shift and start hiring for it now will have a meaningful competitive advantage. The ones that wait for the market to mature will find themselves competing for talent that’s already been claimed.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>Here’s where the jobs are, what they’re paying, and what surprised us.
No surprise here — AI-related hiring in Austin continues to accelerate. But the nature of the roles is shifting. In 2024, companies were hiring AI researchers and data scientists. In 2026, they’re hiring AI engineers who can deploy and maintain production systems, AI product managers who can translate capability into business value, and AI governance specialists who can manage risk and compliance.
Roles in highest demand:
What’s cooling off: Entry-level data analyst roles are seeing less demand as AI tools handle more routine analysis. Mid-level software engineering without AI specialization has also slowed.
Austin’s healthcare sector is in a genuine expansion phase. The combination of population growth, medical infrastructure investment, and a growing cluster of health-tech startups is creating sustained demand across clinical and non-clinical roles.
Roles in highest demand:
What surprised us: The speed at which telehealth infrastructure roles have grown. Remote patient monitoring, virtual care platforms, and digital health operations are creating a new category of roles that didn’t exist three years ago.
Texas is the largest producer of wind energy in the United States, and Austin is increasingly becoming a hub for clean energy companies. Solar, battery storage, and grid modernization are all driving hiring activity.
Roles in highest demand:
What surprised us: The crossover between tech and energy. Companies are hiring software engineers and data scientists specifically for energy optimization and grid management applications. These roles pay tech-level salaries but sit within energy companies.
Austin’s financial services sector has grown quietly but significantly. A mix of fintech startups, regional bank headquarters, and corporate finance functions at tech companies are all contributing to demand.
Roles in highest demand:
What surprised us: The convergence of finance and AI. Companies want finance leaders who can implement AI-powered forecasting and automate reporting workflows. This hybrid profile commands a 15-20% premium over traditional finance roles.
State government agencies in Austin and the growing defense technology sector in the broader Central Texas region are hiring at levels we haven’t seen in years.
Roles in highest demand:
What surprised us: State government salaries have become genuinely competitive for certain roles, particularly in cybersecurity and data. When you factor in benefits, pension contributions, and job stability, the total compensation package rivals many private-sector offers.
The pattern that cuts across all five sectors is the same: every industry is hiring for AI-adjacent capabilities. Whether it’s healthcare, energy, finance, or government, the roles that are growing fastest are the ones that combine domain expertise with technical fluency.
If you’re a candidate, this is good news. Domain expertise doesn’t become less valuable in an AI world — it becomes more valuable when paired with the ability to leverage AI tools effectively.
If you’re a hiring manager, the takeaway is that you’re competing for talent across sectors, not just within your own. The AI product manager you want might also be getting offers from a healthcare company, a fintech, and a clean energy startup. Your pitch needs to account for that.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>We don’t do that.
Not because we think technology is bad — we use AI tools every day, and we believe they make us better at what we do. But because the core of recruiting isn’t matching keywords to job descriptions. It’s understanding people. And that part hasn’t been automated, and we don’t think it should be.
This is what we believe.
Before we present a candidate to a client, we’ve had a real conversation with them. Not a five-minute screen. A substantive discussion about what they’ve done, what they want to do next, what matters to them in a role, and what they’re not willing to compromise on.
This takes time. It means we work with fewer candidates than a high-volume firm. But the result is that when we make an introduction, it’s grounded in actual understanding — not pattern matching.
We’ve heard too many candidates describe their experience with other recruiters as transactional: “They didn’t even read my resume.” We read it. We ask about it. We care about the story behind it.
Recruiting is a relationship business, and relationships require trust. We don’t share a candidate’s information without their permission. We don’t submit resumes to companies without telling the candidate first. We don’t play games with competing offers.
These sound like basic professional standards, and they should be. But anyone who’s spent time in this industry knows they’re often not followed. We follow them because they’re right — and because our reputation depends on the integrity of every interaction.
When a candidate trusts us with their career search, that’s a significant act of trust. We take it seriously.
Every message we send is intentional. If we’re reaching out to you, it’s because we’ve looked at your background and believe there’s a genuine fit with a specific opportunity. We don’t send mass emails with “[First Name]” placeholders. We don’t add people to drip campaigns without their consent.
This approach limits our reach, and we’re fine with that. We’d rather have meaningful conversations with a hundred people than send irrelevant messages to ten thousand.
Our job isn’t just to fill a role — it’s to advocate for both sides of the equation. For candidates, that means presenting their strengths honestly, preparing them thoroughly, and pushing back on processes that aren’t fair or reasonable. For clients, it means being honest about the market, setting realistic expectations, and delivering candidates who genuinely fit — not just candidates who look good on paper.
Advocacy sometimes means telling a client something they don’t want to hear: that their timeline is too slow, their compensation is below market, or their interview process is driving away the candidates they want. We do this because our credibility depends on honesty, not on telling people what they want to hear.
We’re in a moment where AI is transforming every industry, including ours. And that transformation is overwhelmingly positive — it helps us find candidates faster, understand market trends in real time, and produce better research for our clients.
But the temptation to let technology replace the human elements of recruiting is real. To let AI write the outreach, score the candidates, and automate the follow-up. Some firms are going that direction, and for certain kinds of high-volume, low-complexity hiring, it might work.
That’s not our market. We work with companies that have specific, high-stakes hiring needs — roles where the wrong hire costs real money and real momentum. In those situations, there is no substitute for human judgment, relationship, and care.
People are the center of our business. The people we recruit, the people we recruit for, and the people on our team who make it all work. That’s not a tagline. It’s how we operate, every day.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>Here’s what we’re actually seeing from the top of the pile.
The single biggest shift: top candidates have stopped listing what they were responsible for and started leading with what they accomplished. This sounds obvious, but the execution matters.
Weak: “Responsible for managing a team of 12 analysts and overseeing quarterly reporting.”
Strong: “Led a 12-person analytics team that reduced reporting cycle time by 40% and identified $2.3M in cost savings through predictive modeling.”
The second version tells a hiring manager exactly what you did and why it mattered. Every bullet on a strong resume answers the question: “So what?”
The best candidates aren’t just writing “familiar with AI tools.” They’re listing specific platforms and specific outcomes. We’re seeing lines like:
This specificity does two things: it demonstrates real experience (not just awareness), and it gives the hiring manager something concrete to ask about in the interview. That’s what a great resume does — it creates conversation starters.
The objective statement is finally, mercifully, dying. Top candidates have replaced it with a two-to-three line professional summary that functions as a value proposition. Not what you want from the company — what the company gets by hiring you.
We’re seeing formats like: “Operations leader with 10 years of experience scaling logistics functions at high-growth companies. Built and led the supply chain team at [Company] from 3 to 25 people during a period of 4x revenue growth. Deep expertise in AI-driven demand forecasting and vendor management.”
That’s useful. An objective statement like “Seeking a challenging role where I can leverage my experience” tells us nothing.
Applicant Tracking Systems are still the first gate most resumes pass through, and candidates are getting smarter about designing for them. The changes are practical:
The candidates who understand ATS optimization get through the filter. The ones with beautifully designed but poorly structured resumes often don’t — regardless of how qualified they are.
This is the one that separates the top 10% from everyone else. The best candidates we work with maintain a master resume and create tailored versions for each application. Not a complete rewrite — but strategic emphasis shifts.
If a job description emphasizes team leadership, their leadership accomplishments move to the top. If it emphasizes technical skills, their technical projects lead. If the company is going through a transformation, their transformation experience becomes prominent.
This takes time, and most people don’t do it. That’s exactly why it works.
From the recruiter’s side, here’s what causes us to move past a resume quickly:
Your resume isn’t a career autobiography. It’s a marketing document — and like any marketing document, it needs to be targeted, concise, and focused on value to the reader. The best candidates understand this intuitively. They write their resumes for the person reading them, not for themselves.
If your resume hasn’t been updated in six months, it’s already behind. The market moves fast, and the way you present yourself needs to keep pace.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
]]>If you’re a hiring leader without a deep technical background, you’re not alone in feeling uncertain. The AI model landscape has exploded, and keeping track of who built what — and why it matters — is genuinely hard.
This guide is for you. No jargon. No hype. Just what you need to know to make better hiring decisions.
Anthropic is an AI safety company founded by former OpenAI researchers. Their model, Claude, has become the go-to choice for many enterprises that prioritize safety, accuracy, and long-form reasoning. Claude is known for producing careful, well-structured outputs and handling complex instructions with nuance.
Where it shows up in enterprise: Legal document analysis, financial research, internal knowledge management, code generation, and customer-facing applications where accuracy matters more than speed.
What it means on a resume: A candidate who’s worked with Claude likely has experience in settings where precision and safety guardrails matter — often enterprise or regulated environments.
OpenAI is the most recognized name in AI, largely because of ChatGPT. GPT-4o is their flagship model, capable of processing text, images, and audio. It’s the Swiss Army knife of AI models — broadly capable and widely deployed.
Where it shows up in enterprise: Content generation, customer support automation, data analysis, coding assistance, and multimodal applications that combine text with images or voice.
What it means on a resume: GPT experience is the most common. It tells you the candidate has engaged with AI, but it doesn’t by itself signal depth. Ask what they built with it.
Google’s Gemini models are tightly integrated with Google’s ecosystem — Workspace, Cloud, Search. Their strength is in applications that need to work across Google’s product suite and in scenarios requiring real-time information retrieval.
Where it shows up in enterprise: Companies heavily invested in Google Cloud Platform, applications requiring search integration, and multimodal use cases that leverage Google’s data infrastructure.
What it means on a resume: Often signals the candidate works in a Google-centric environment. Worth asking about the specific Gemini applications they’ve used.
Meta’s Llama models are open-source, which means anyone can download, modify, and deploy them. This is a fundamentally different model from the others on this list — it’s not a service you pay for, it’s software you run yourself.
Where it shows up in enterprise: Companies that need to run AI models on their own infrastructure for privacy, compliance, or cost reasons. Common in healthcare, defense, financial services, and any organization that can’t send data to external APIs.
What it means on a resume: A candidate with Llama experience likely has deeper technical chops. They’ve dealt with model deployment, infrastructure, and potentially fine-tuning — not just prompting.
Mistral is a French AI company that has gained a strong reputation for efficient, high-performance models. Their models punch above their weight — delivering strong results with less computational overhead than larger competitors.
Where it shows up in enterprise: Cost-conscious deployments, European companies with data sovereignty requirements, and applications where inference speed and efficiency matter.
What it means on a resume: Signals technical sophistication and awareness of the broader AI ecosystem beyond the big American players.
Here’s the honest truth: for most non-technical roles, the specific model a candidate has used matters less than how they’ve used it. The questions that reveal real capability are:
“What did you build or automate with AI?” — You want specific use cases, not general familiarity.
“How did you evaluate whether the AI output was good enough?” — This tells you about judgment, not just tool usage.
“What didn’t work, and what did you do about it?” — This separates people who’ve genuinely worked with AI from those who’ve only experimented casually.
“How did you decide which model or tool to use?” — This is the gold standard question. If a candidate can articulate why they chose Claude over GPT for a specific task — or vice versa — they have real working knowledge.
You don’t need to become an AI expert to hire well in 2026. But you do need to understand the landscape well enough to ask informed questions. When a candidate says “AI experience,” don’t nod and move on. Ask which tools, what outcomes, and what they learned.
The best candidates will appreciate the question. The ones who can’t answer it in specifics probably aren’t as fluent as their resume suggests.
Scherer Talent is a boutique recruiting firm based in Austin, TX. We specialize in digital transformation, technology, and leadership roles. Schedule a call to discuss your search.
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