📍 In-Office
AI Agent Engineer jobs
AI Agent Engineers turn LLMs into systems that take actions. They design tool-use interfaces, planning and reasoning loops, memory, and the evaluation harnesses that keep agents reliable in production. Expect strong software engineering fundamentals paired with hands-on experience wiring models to real tools and data.
Also called
AI Agent Engineer · Agent Engineer · Autonomous Agents Engineer · LLM Agent Engineer · Applied AI Engineer (Agents) · Agentic AI Engineer
Key skills
Python / TypeScript · LLM tool use & function calling · Agent frameworks · Evals & observability · RAG
What a AI Agent Engineer does
- •Design tool-use interfaces and function-calling schemas that let agents act on real systems
- •Build planning/reasoning loops (ReAct, plan-and-execute) and short- and long-term memory
- •Write and maintain eval suites that catch regressions in non-deterministic behavior
- •Integrate retrieval (RAG) and external APIs/MCP servers as agent capabilities
- •Harden agents for production: retries, guardrails, cost and latency budgets
Leveling
- Junior
- Ships well-scoped tools and prompts under guidance; writes evals for a single agent.
- Mid
- Owns an agent end-to-end: tool design, memory, evals, and production reliability.
- Senior
- Designs multi-step agent systems, sets eval standards, mentors, and drives reliability.
- Staff+
- Defines agent patterns across teams; bridges into architecture and platform decisions.
Salary by level
Full salary breakdown →Junior
$120k–$160k
Mid
$155k–$205k
Senior
$190k–$260k
Staff+
$250k–$350k
US total-cash ranges synthesized from aggregated public job postings and market data as of 2026. Individual offers vary widely by location, company stage, and equity; treat these as directional bands, not guarantees.
Open AI Agent Engineer roles (4)
Search & filter →📍 In-Office
📍 Hybrid
📍 Hybrid
AI Agent Engineer FAQ
- What does an AI agent engineer do?
- They build software systems that use LLMs to take actions — designing tool use and function calling, planning loops, memory, and the evaluation harnesses that keep agents reliable in production.
- What skills do you need to become an AI agent engineer?
- Strong software engineering (usually Python or TypeScript), hands-on LLM tool use / function calling, familiarity with an agent framework like LangGraph or CrewAI, RAG, and eval-driven development for non-deterministic systems.
- How much does an AI agent engineer make?
- In the US, total-cash ranges run roughly $120k–$160k (junior), $155k–$205k (mid), $190k–$260k (senior), and $250k–$350k+ (staff and above), varying by location, stage, and equity.
- Is AI agent engineer the same as AI engineer?
- Overlapping but not identical. 'AI engineer' is a broad title; agent engineering is the subset focused specifically on autonomous, tool-using agents — planning loops, memory, and agent evals.
Learn more
- How to Become an Agentic AI Engineer
A practical, step-by-step path to becoming an agentic AI engineer: fundamentals, LLM APIs, agent frameworks, RAG, evals, and a portfolio project.
- What Is an AI Agent Engineer?
A clear definition of the AI Agent Engineer role: what they build, the skills employers expect, salary ranges, and how the title differs from a classic AI/ML engineer.