Job description
We're building production AI agents that change how our engineering org ships code and how employees work with internal knowledge.
You'll join a small, high-ownership team.
You'll write the agent logic, the tools, the data layer, and the pipelines that make them dependable at scale.
Turn architecture into reliable, well-tested, production-grade systems.
Role and Responsibilities : Implement agent logic, tools, and orchestration against the given architecture.
Build and tune RAG pipelines : ingestion → embeddings → retrieval → re-ranking → evaluation Design and optimize Postgres schemas, queries, and vector indexes for production load Build the test-generation and test-execution engine for the AI Code Pipeline Integrate with Git, CI/CD, and internal services Build evaluation harnesses, observability, and guardrails so agents are measurable and safe Own the reliability, latency, and cost of the systems you ship Write clean, typed, well-tested Python and participate actively in code review Opportunity to work for a dynamic international company with a flat hierarchical structure, where your voice matters and your impact is seen.
4+ years of professional software engineering in Python , with deep, hands-on command of the language : async, typing, packaging, performance, and clean, maintainable code 1+ years building LLM / agentic systems — tool use / function calling, orchestration, prompting, and evaluation Strong problem-solving and debugging on ambiguous, real-world production problems.
Solid Postgres experience: schema design, query optimization, and extensions ( pgvector ) Experience shipping and operating production services — testing, CI/CD, observability, on-call mindset Comfort with Git-based workflows and code review Automating software testing: unit, integration, functional, security, performance Integrating with developer tooling and CI/CD systems 6+ months of demonstrated experience building with Claude Code in a development workflow
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