Tech talent on the move, senior AI jobs, MLOps & more...February update!

Spring is almost within reach as we close in on March, and the AI talent market is heating up even faster than the weather! At People In AI, we've been busier than ever, connecting exceptional candidates with forward-thinking clients across every level from IC to C-suite.

Some exciting team news: Sam Agre has joined People In AI and hit the ground running with multiple placements, new retainers, and over $100K in billings in just his first full month! And yes, his beloved Eagles won the Super Bowl, so he's absolutely crushing it on all fronts. If you're looking to build out your team, connect with Sam Agre - his track record speaks for itself.

In this newsletter, we're diving into the most significant trends we're seeing in Q1 2025 - from traditional industries attracting top tech talent to the post-bonus leadership shuffle that's reshaping executive teams across the industry.

Old Money, New Tech: Why Wall Street and Healthcare Are Stealing Silicon Valley's Best Talent

Banking & Healthcare: Not Your Parents' Boring Industries Anymore

The talent migration happening right now is fascinating to watch. We've placed multiple senior engineers in healthcare and finance last month alone – all leaving prestigious tech roles for industries they wouldn't have considered two years ago.

What's driving this shift? For starters, these established industries have accumulated decades of proprietary, regulated data. As one banking client put it: "Our transaction data goes back 30 years. You simply can't replicate that kind of resource."

Compensation packages have evolved dramatically, too. Traditional industries are offering competitive base salaries plus meaningful equity and, crucially, better work-life balance. Several candidates have mentioned the appeal of solving complex AI problems without the burnout culture they experienced elsewhere.

Leadership Movement Picks Up As Q1 Bonuses Land

Executive movement has accelerated significantly with bonuses almost cleared and 2025 budgets finalized.

We've had conversations with multiple CTOs and AI Directors who successfully launched initiatives and are now looking for new challenges. They're capitalizing on their track records to step into more strategic roles at companies beginning their AI journeys.

Companies that were hesitant in December have suddenly become aggressive. One client who was "still finalizing headcount" in Q4 just approved five senior AI positions with notably competitive compensation bands.

ML Engineers: The Supply-Demand Imbalance Intensifies

The market for ML talent has reached unprecedented tightness, driven by two converging trends:

First, companies that implemented LLMs last year are discovering they need specialized talent to customize and maintain these systems. As one hiring manager told me: "We got the quick wins from API integration, but now we need people who understand how to actually engineer solutions around these models."

Simultaneously, organizations planning their AI roadmaps are staffing up before launching initiatives – they've seen the chaos of hasty implementation and are building teams first.

The result? Experienced ML Engineers are receiving multiple competitive offers, often with 48-hour decision windows, and I'm seeing compensation increase by roughly 20% year-over-year.

MLOps: The Unsung Heroes Finally Getting Recognition

Perhaps the most significant shift I'm seeing: companies recognizing the critical importance of MLOps engineers.

As organizations scale from a handful of models to dozens in production, the infrastructure challenges become exponential. Data scientists and ML engineers end up spending most of their time fighting operational issues rather than delivering value.

A client recently described their MLOps hire as "the force multiplier for our entire data science team." When you're paying premium salaries for senior AI talent, having them blocked by infrastructure problems becomes prohibitively expensive.

What's telling: I'm placing experienced backend engineers who've pivoted to MLOps, drawn by the challenge and compensation. As one such engineer told me: "Everyone's chasing the latest LLM breakthroughs, but the real shortage is in people who can build reliable AI infrastructure."