Key Takeaways
- AI engineering roles require specialized skills beyond general software engineering — technical vetting is non-negotiable
- The average time-to-fill for AI engineers is 60-90 days without a specialist recruiter
- People in AI delivers qualified candidates within 3 business days of your job brief
- The right AI engineering hire can accelerate your product roadmap by 6-12 months
Why Hiring AI Engineers Is Harder Than It Looks
The demand for AI engineers has outpaced supply by more than 5:1. Every Series B startup, every Fortune 500 AI initiative, and every mid-market tech company is competing for the same small pool of candidates who can design, build, and deploy AI systems at scale.
General-purpose technical recruiters struggle here for one reason: they cannot evaluate candidates. Without the ability to assess framework proficiency (PyTorch, TensorFlow, JAX), production ML experience, and architectural judgment, job descriptions attract the wrong candidates and great engineers get missed.
People in AI exists to solve this problem. Our recruiters understand the difference between an AI engineer who trains models in notebooks and one who builds production inference pipelines, and your hiring process reflects that distinction.
What to Look For in an AI Engineer
When hiring AI engineers, the skill set you need depends on where they sit in your stack. Here are the core profiles:
Applied AI Engineer
Builds and deploys AI features into production applications. Strong Python, ML framework experience, API integration, and the ability to own the full model-to-product pipeline.
ML Platform / MLOps Engineer
Owns the infrastructure that makes AI scale: feature stores, model registries, CI/CD for ML, monitoring, and serving. Look for Kubeflow, MLflow, and cloud ML platform experience.
Research Engineer
Bridges cutting-edge research and production engineering. Requires a strong publication background or open-source contributions alongside solid engineering fundamentals.
Foundational AI Engineer
Works on the core model: pretraining, fine-tuning, RLHF, and optimization. Rare, expensive, and in extreme demand. Best sourced through specialist networks, not job boards.
Salary Benchmarks for AI Engineers (2025)
Compensation varies significantly by role type and location. Here are current market ranges People in AI places at:
- Applied AI Engineer (Senior): $180,000 to $240,000 base
- ML Platform Engineer: $190,000 to $260,000 base
- Research Engineer: $220,000 to $350,000+ base
- AI Tech Lead / Staff Engineer: $250,000 to $400,000 base
Equity (0.1% to 1.0% for senior hires) and signing bonuses are standard expectations in this market. Coming in below market by 10-15% will cost you 60-80% of your candidate pipeline.
The People in AI Hiring Process
Our 3-day candidate delivery promise is not a marketing claim. It is an operational reality driven by a pre-built, actively maintained network of AI engineers across North America.
- Day 1 — Job Brief Call: 45-minute session to define must-haves, dealbreakers, team context, and technical bar
- Day 2 — Shortlist Build: We surface and screen candidates from our active network, not passive job board applicants
- Day 3 — Candidate Presentation: You receive 2-4 fully screened candidates with technical assessment notes and compensation expectations
- Week 2 — Interview Coordination: We manage scheduling, prep candidates, collect feedback, and accelerate decision-making
- Offer and Close: We handle negotiation and first-week onboarding hand-off
Common Mistakes Companies Make When Hiring AI Engineers
Writing job descriptions for data scientists, not engineers. AI engineers build systems. Keep requirements technical and production-focused.
Requiring a PhD when you need a builder. For most product-facing AI roles, a strong GitHub profile matters more than academic credentials.
Moving too slowly. Top AI engineers receive multiple offers simultaneously. A 3-week interview process loses candidates. Compress your loop or work with a recruiter who can hold candidates in your pipeline.
Under-compensating. The market has priced this talent. Trying to hire at a 20% discount to market means hiring your 10th-best option.
Ready to Hire Your Next AI Engineer?
People in AI has placed AI engineers at companies ranging from seed-stage startups building their first ML team to enterprise organizations scaling existing AI capabilities. We know where the talent is, we have the relationships to move fast, and we understand the technical bar your role requires.
Submit your job brief today and receive your first shortlist within 3 business days.
