Software Engineer, Engineering Platform

Build systems that make 300 engineers faster — merge queues, dev deploys, CI/CD, Smart Reviewer, stack tooling — and own the blast radius when things slow down

Lead important incidents end-to-end: diagnose root cause (DB serialization failures, Redis latency spikes, Temporal timeouts), fix it, write the postmortem, and prevent the next one

Design golden paths for services — API, DB migrations, Kafka, Temporal, secrets — so teams can spin up infrastructure without reinventing the wheel every time

Own the full dev tooling surface: Devportal, Graphite, Buildkite, Inspect, dev deploys, LaunchDarkly, Datadog — and understand how they interact under pressure

Treat the SDLC as a factory: measure PR throughput, CI/CD end-to-end time, and defect rates, then fix the bottlenecks instead of just monitoring them

Turn recurring developer friction — flaky tests, spicy migrations, ECR credential expiry, devtool onboard failures — into one-time fixes, not on-call rituals

Build agent-friendly infrastructure: golden paths, documentation, and tooling so AI coding agents can execute tasks correctly without a human untangling Temporal, migrations, or feature flags

Build AI-native reliability tooling — on-call automation, review agents, autonomous testing — and design clean handoffs from AI investigation to human-authorized action

Think at the system level about tech debt: feature flag cleanup, dead code deletion, punchlist orchestration — because dead code confuses agents and humans equally

You think in systems: you understand how a 400-connection pool cap, a Redis replica for feature flag cache warmup, and a Cloudflare worker change interact under load

You've built and operated CI/CD infrastructure, developer tooling, or platform systems at meaningful scale

You're comfortable diagnosing production failures at the infrastructure layer — connection pools, serialization issues, cache misses, distributed timeouts

You have strong opinions about software architecture and don't confuse them for facts — you know when to ship the 80/20 and when to slow down and design it right

You use AI as a force multiplier — coding agents, agentic testing, AI-augmented code review — and you're building the infrastructure that makes that possible, not threatened by it

You care deeply about the reliability of prod, the experience of other engineers, and the quality of what you ship

Experience with our stack is a plus: Python, Temporal, Kafka, PostgreSQL, Redis, Buildkite, LaunchDarkly, Datadog, AWS

If you are being referred for the role, please contact that person to apply on your behalf.

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