Software Engineering Lead Data Services

Read this first. This role is not for you if:

• You want to manage people more than write code. This role is 80% hands-on engineering 20% leading the team

• Youve never had engineers formally reporting to you. Mentoring or acting as a tech lead without direct reports doesnt count

• You havent built production services with FastAPI

• You havent written production code in the last year

• Your AI experience is wrapping an LLM API in a prototype not running agents in production with evals and traces

• Youve never built the harness agents run inside: tool calling MCP servers eval suites

• You havent run services handling millions of API calls

• Your experience is mostly services or consulting delivery without long-term ownership of a product

Firmable sells company and people data to sales teams across Asia Pacific and the US and were taking it worldwide. Data Services builds the APIs services and agents behind every Firmable product and this role runs it.

Youll lead one engineering pod.

• Python service and API architecture on FastAPI Pydantic and Logfire

• The agent runtime the team builds on: tool calling MCP servers structured-output validation bounded loops human checkpoints and replayable traces

• Fast decision APIs built on small typed models next to LLM agents for the work that needs real reasoning

• Evals in CI: labelled sets judge calibration multi-turn and trajectory tests drift detection

• Reliability at scale: caching rate limits cost ceilings retries and graceful degradation

• Architecture and code review across both pods

• 710 years of backend engineering

• Expert Python plus data modelling across SQL and NoSQL

• RESTful services you designed and ran at scale

Nice to have: Braintrust Inspect or Promptfoo Logfire or OpenTelemetry Claude Agent SDK Pydantic AI or LangGraph AWS or GCP at scale Snowflake B2B data startup experience

We write code with coding agents like Claude Code by default and engineers spend their time on design review and production we pick the model for the job: frontier LLMs for messy extraction and reasoning small typed decision models when the answer is a yes/no a choice or a score and MCP servers and agent SDKs when a model needs tools. When something new ships we run it against our evals that week. Every LLM call is logged with its prompt version model and cost.

Small teams no layers weekly releases moving to daily. No fixed hours no handholding.

Competitive base and meaningful equity. The next version of our services and agent platform is yours to design.

Firmable is an equal opportunity employer. We believe diverse teams build better products.