Related skills
redis postgres python kubernetes fastapi📋 Description
- Architect agentic systems for the Investigation Agent: LangGraph and tooling.
- Own context engineering as a discipline: define what the agent sees and when.
- Build feedback loops, eval harnesses, and tracing to measure progress.
- Make architectural decisions on agent state, long-running workflows, and safety.
- Own backend work end-to-end: Python, FastAPI, Postgres, Redis, Kubernetes.
- Collaborate with Product/UX, Data Science, and Engineering to shape features.
🎯 Requirements
- 5+ years of professional software engineering, Python backend, production systems.
- Hands-on design and building of agentic systems: multi-step workflows, context, memory, evaluation.
- Strong intuition for context engineering, prompt design, eval design, and LLM failure modes.
- Solid backend fundamentals: FastAPI, Postgres, Redis, Kubernetes, observability.
- Hands-on fluency with agentic tools (Claude Code, Cursor) daily.
- Excellent problem solving; shape product & architecture; strong communicator.
🎁 Benefits
- Production experience with Langfuse or similar LLM observability tools.
- Experience in Anti-Financial Crime (AML, fraud) domain.
- Shipped agentic products to real users in production.
Meet JobCopilot: Your Personal AI Job Hunter
Automatically Apply to Engineering Jobs. Just set your
preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.
Help us maintain the quality of jobs posted on Empllo!
Is this position not a remote job?
Let us know!