• Design, build, and operate backend services in Python that power AI-driven products and shared capabilities. • Build and maintain resilient service integrations across internal and external systems, handling failure modes, rate limits, and interface changes. • Own ambiguous, end-to-end problems: from early design and architecture through implementation, rollout, and iteration in production. • Develop and evolve LLM-backed features and agentic workflows used in production, with a focus on reliability, observability, and real-world behavior. • Contribute to core AI platforms and enablement systems—services that your team uses directly and that other engineers can build on. • Collaborate with product managers, researchers, and other engineers across teams to turn loosely defined AI use cases into concrete, production-ready systems. • Help shape evaluation and quality strategies for AI-powered features, including building or extending evaluation harnesses, benchmarks, or feedback loops. • Act as a technical leader for the work you own—making sound design decisions, coordinating with stakeholders, and contributing to design and code reviews.