Design and ship integrations that LLMs can use effectively
Design tool APIs with attention to schema clarity, error message quality, and idempotency — agents reason about your responses, so wording and structure matter
Own each integration end-to-end: auth, rate limiting, retries, safe defaults for destructive or sensitive operations, and observability
Write focused tests, including contract tests against the upstream services you integrate with
Build the platform around the integrations
Define and evolve the internal template for adding new tools — the catalog will grow, and the second integration should be cheaper than the first
Instrument every tool with metrics, logs, and traces from day one; usage by agents is the primary signal we operate on
Package, deploy, and operate the service in AWS/Kubernetes (EKS)
Translate agent needs into stable backend contracts; push back when "what the agent wants" and "what the system can promise" disagree
Prioritise the tool catalog with AI Engineers as primary customers
Document the path for domain teams to contribute their own tools as the layer matures

Senior-level Python backend experience (5+ years), with services you have shipped, operated, and been on-call for
Experience designing and operating microservices (FastAPI or similar)
Hands-on experience with Docker and Kubernetes
A platform mindset: your users are other engineers, and your API design reflects that

Would be a big plus:

Prior work with LLM tool-calling / function-calling / agent frameworks (MCP, OpenAI/Anthropic tool use, LangChain, or similar) — or strong curiosity about this space
Strong API design background: OpenAPI, contract testing, SDK ergonomics, schema evolution
AWS and Terraform experience
Understanding of concurrency models in Python (asyncio, multiprocessing, threading)
Fintech, payments, or risk domain exposure

Python Developer

Key skills