AI Agent Architect
Design and build AI-agent workflow architecture, integrate and fine-tune models, establish reliability and observability standards, build evaluation tooling, and make documented architectural decisions for production enterprise systems.
Responsibilities
- Design and build AI-agent workflow architecture, including planning, tool use, memory, retrieval, and human checkpoints.
- Evaluate, integrate, and fine-tune foundation models and LLM APIs.
- Define standards for agent reliability, observability, and production failure modes.
- Translate client deployment learnings into reusable platform components.
- Build evaluation harnesses for agent quality, hallucination rates, and task completion.
- Make principled, documented architectural decisions.
Requirements
- 6–10 years building production AI or data systems.
- Deep hands-on experience with multi-agent architectures.
- Strong Python skills and familiarity with agent frameworks such as LangChain, LlamaIndex, or AutoGen.
- Production experience with RAG architectures, vector databases, and context window management.
- Experience deploying LLM-powered systems in enterprise contexts.
- Knowledge of data security, access controls, and audit logging.
Benefits
- Meaningful early-stage equity
- Remote work