Design, build, and maintain critical backend systems across capture services, shared platform models, event pipelines, async workers, APIs, and AI/intelligence workflows.
Lead technical execution for ambiguous, high-impact projects that span multiple services or domains.
Work directly in systems that ingest and normalize communications data from platforms like Microsoft, Slack, Zoom, Google, Bloomberg, Salesforce, Proofpoint Archive, and other enterprise sources.
Contribute to AI-native product surfaces including LLM classification, agent runs, investigator workflows, telemetry, evaluations, and future decision-tracing capabilities.
Improve reliability, observability, testability, and operational maturity across a fast-moving production codebase.
Debug difficult customer and production issues involving data correctness, API behavior, async failures, scale, performance, and compliance-sensitive workflows.
Mentor engineers through design review, code review, pairing, technical writing, and clear architectural judgment.
Requirements
8+ years building production backend or full-stack systems, with Staff-level ownership of large or ambiguous technical areas.
Strong Python experience, including typed code, data modeling, testing, and production debugging.
Deep experience with relational databases, especially Postgres, schema design, query performance, migrations, and data correctness.
Experience building distributed or asynchronous systems involving queues, workers, retries, idempotency, rate limits, and failure recovery.
Strong API integration experience, ideally with OAuth, webhooks, pagination, throttling, vendor-specific edge cases, and long-running backfills.