Design, build, and ship production-quality backend services, APIs, and AI platform components used across multiple engineering teams
Build and integrate LLM-powered systems such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, prompt/tool orchestration, and model observability
Improve the reliability, scalability, observability, and operational quality of production AI systems
Build internal tools, frameworks, automation, and documentation that improve developer productivity and AI capabilities
Participate in code reviews, design reviews, debugging, incident response, and operational support
Contribute to technical design for complex projects, including evaluating tradeoffs and proposing pragmatic implementation plans
Partner with product, design, and engineering teams to translate platform needs into well-designed technical solutions
Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle
Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards
Use agentic coding tools and LLM-assisted development as a primary part of your workflow — this is how the entire team operates
Critically evaluate AI-generated code for correctness, edge cases, and regressions — shipping quality output regardless of how it was produced
Contribute to the team's evolving practices around AI-accelerated development and testing

5+ years of experience designing, building, and operating production software systems
Strong backend engineering experience with Python frameworks such as FastAPI, Flask, or Django
Experience building or integrating AI/LLM-powered systems in production
such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, or agentic workflows
Experience with relational/NoSQL databases, including schema design, query optimization, and data modeling
Experience with cloud-native technologies such as AWS, Docker, and Kubernetes
Strong understanding of CI/CD, observability, and operating services in production
Ability to break down complex technical problems and deliver pragmatic, maintainable solutions
Strong ownership mindset, with the ability to drive projects independently while collaborating effectively
Clear communication skills and the ability to explain technical tradeoffs to engineering and cross-functional partners
Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate velocity and code quality
Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases

Senior Software Engineer, AI

Key skills