Staff Software Engineer

10+ years of software engineering experience, with at least 2 years in a staff-level role or functioning at that scope.

Deep expertise in at least one technical area: backend systems, platform engineering, cloud infrastructure, data engineering, or AI/ML integration.

A proven history of designing and shipping complex software systems end-to-end — not just features, but systems that other teams depend on.

Strong debugging and troubleshooting skills; you can root-cause a hard production problem under pressure.

Solid across the full modern software stack: microservices, APIs, relational and non-relational databases, event streaming, cloud platforms, and container orchestration.

Proficient in at least one backend language (Java, Go, Python, Node.js, or similar); experience with polyglot environments is a plus.

Hands-on with Kubernetes, Helm, Terraform, and modern CI/CD (GitHub Actions, ArgoCD, or equivalent).

Working knowledge of observability practices — distributed tracing, structured logging, SLO/SLA-based alerting (Datadog, OpenTelemetry, Prometheus).

Exposure to AI/ML ecosystems: REST APIs for LLMs, prompt engineering, vector search, or embedding pipelines.

Actively uses AI-powered developer tools (Copilot, Claude Code, or similar) as part of daily development — not occasionally, but habitually.

Can articulate when AI-generated code should be trusted, reviewed carefully, or discarded entirely.

Interest in building AI-native product features: integrating LLM APIs, building agent-backed workflows, or wiring AI into user-facing products.

Bias for action: you get to working solutions quickly, iterate, and improve rather than waiting for perfect requirements.

Cross-functional collaborator — you've worked across engineering, product, design, data, and ops to ship things that matter.

Comfortable operating under ambiguity: you can scope undefined problems, propose solutions, and drive alignment without a fully defined spec.

Strong written and verbal communication; you can explain a complex system to both engineers and non-engineers.

Experience in the automation, workflow, or enterprise software space.

Familiarity with agentic AI frameworks (LangChain, LlamaIndex, AutoGen) or multi-agent system design.

Experience building developer-facing platforms, SDKs, or internal tooling.

Open-source contributions or public technical writing.