AI Engineer
Builds generative-AI products and features: agents, RAG, LLM integrations — with a software engineer's rigor.
Why this hire matters.
The AI engineer is the profile that emerged with LLMs: a software engineer who builds with models rather than training them. It's the central role of the current wave — agents, copilots, intelligent automation — and the one that determines whether your AI product is a differentiator or a fragile wrapper a competitor replicates in a weekend. Their craft: agent architectures (orchestration, tools, memory), RAG that actually works on your data, systematic evaluation, and the art of composing models with classical software. The market is saturated with candidates who have 'played with ChatGPT': filter on systems shipped to production, evaluation culture and understanding of model limits. It's the most frequent — and most poorly calibrated — AI hire of the moment.
Key missions.
- Design and build LLM-based features (agents, copilots, RAG)
- Architect agent systems (orchestration, tools, memory)
- Set up continuous evaluation of AI features
- Optimize quality, cost and latency of model calls
- Integrate AI into the existing product and infrastructure
- Prototype fast, then industrialize what works
- Track the rapid evolution of models and patterns
Skills.
Technical skills
- Solid software engineering (TypeScript/Python)
- Agent architectures and function calling
- RAG, embeddings, vector databases
- LLM evaluation and observability
- API fluency (Anthropic, OpenAI, Mistral)
Expected qualities
- Learning speed
- Product sense
- Judgment on AI's limits
Common stack
Salaries 2025-2026
| Level | Experience | Annual gross base |
|---|---|---|
| Junior | 0-2 yrs | 50–65 k€ |
| Mid-level | 2-5 yrs | 65–90 k€ |
| Senior | 5-8 yrs | 85–120 k€ |
| Lead / Staff | 8+ yrs | 120–180 k€ |
Paris market ranges, 2025-2026.
Outside the Paris region, expect 10 to 20 % less.
Sources : Silkhom 2026 · Get in Talent 2026 (fourchette 65-180k) · Michael Page 2026
Hiring this profile.
Typical background
Full-stack or backend developer who pivoted to LLMs, or a product-oriented ML engineer. Very recent role: a portfolio of real projects beats everything.
When to hire
As soon as an AI feature becomes strategic for the product — often a non-AI scale-up's first 'AI' hire, seed to Series B.
Career path
Senior → Staff AI Engineer / Lead → Head of AI Engineering → CTO or Chief AI Officer.