AI Engineer

Responsibilities:

• Design and build multi-step agents using LLMs, tool use, retrieval, and memory, in frameworks like LangChain, LangGraph, or similar.
• Architect single-agent and multi-agent systems: subagents, routing and handoffs, planning, and state management for long-running tasks.
• Build evaluation frameworks for agent behaviour, LLM-as-judge and deterministic evaluators, and use them to iterate on prompts and architecture.
• Integrate agents with client systems and data sources: APIs, databases, vector stores, and MCP or tool integrations.
• Deploy agents to production and set up observability, tracing, logging, and error analysis to monitor real-world behaviour.

Requirements:

• 3-7 years of experience in backend or full-stack engineering, with a track record of shipping production systems.
• Hands-on experience building agents with LLM frameworks (LangChain, LangGraph, or similar), including tool use and multi-step reasoning.
• Experience with prompt engineering and evaluation frameworks, and iterating on agent behaviour using real feedback.
• Strong proficiency in Python and/or TypeScript, APIs, and system design; cloud experience preferred.
• Comfort taking ownership of a project end-to-end, from architecture to a client using it in production.