As a Software Engineer, you’ll prototype quickly, tie engineering to business outcomes, and balance rigor with AI-driven velocity. You’ll build and extend the quality platform—orchestration, retrieval, evaluation harnesses, and APIs—that scales quality across the portfolio
Minimum Qualifications
Requires Bachelor's degree in Computer Science, a technical field or a minimum of 5 years of relevant work experience in the US.
Programming fundamentals demonstrated across multiple projects or large/shared codebases, with the ability to ramp quickly as the stack evolves, including designing asynchronous, event-driven systems — applying concurrency, non-blocking I/O, and sound failure handling at scale.
Experience with RESTful/GraphQL APIs and automated testing frameworks.
Experience either improving liability of shared CI/test infrastructure or operating a CI runner fleet.
Shipped one LLM-powered feature.
Preferred Qualifications
8+ years as a Software Engineer and 5+ years in automation or platform tooling.
Retrieval + RAG expertise (e.g., Pinecone, Qdrant, OpenSearch; re-ranking, hallucination evals,chunking strategies).
Strong Python for ML/LLM workflows; advanced TypeScript and Node for platform services.
Platform integration of AI agents, quality policies, and data-driven dashboards.
Strong fundamentals in mocking, dependency injection, and distributed systems.
Experience building shared execution images/runners and multi-tenancy controls (hardened, versioned images; isolation/quotas; fair queuing) on a company internal cloud (e.g., Kubernetes or an internal scheduler).
Experience with cross-platform automation frameworks across web, native, and APIs; and reducing flakiness and improving time-to-signal via heuristics/stats.
Experience building and integrating REST services, including subgraph/endpoint development, schema/API composition, and deployment collaboration with platform teams.
Experience creating deterministic test data: seeding known records, masked subsets, synthetic data; managing golden dataset versioning and lineage.
Ability to explain complex systems simply to engineers and non-engineers.