Job Description

Locations

• Seattle, Washington, United States 98117

Salary

Skills Required

• architecting systemsintermediate
• building core evaluation frameworksintermediate
• developing AI toolsintermediate
• setting engineering standardsintermediate
• mentoring researchers and engineersintermediate
• deep collaborationintermediate
• understanding user needsintermediate
• ensuring scalabilityintermediate
• translating research into production-ready toolsintermediate

Required Qualifications

• Demonstrated mastery in engineering robust, maintainable, and operable software systems (degree in engineering robust)
• Deep expertise in Python, with demonstrated excellence in designing high-quality, extensible APIs and SDKs (experience)
• Deep experience (5+ years) in platform engineering or adjacent roles, with a proven track record of designing, building, and scaling internal or developer-facing platforms (experience, 5 years)
• Demonstrated track record of driving adoption of developer tools, with experience gathering user feedback and iterating on developer experience (experience)
• Experience with ML development lifecycle and ML platform development, including understanding of model training, evaluation, and deployment workflows (experience)
• Understanding of standard AI stack components such as retrieval systems (vector databases, hybrid search, etc.), model serving platforms, and LLM application frameworks (experience)
• Proven ability to collaborate with cross-functional teams including researchers, engineers, product owners, and leadership (experience)

Preferred Qualifications

• Practical experience building or evaluating applications powered by large language models (e.g., using agentic frameworks, rag, or similar techniques) (experience)
• Experience designing platforms or frameworks that shorten the path from prototype to production (experience)
• Familiarity with distributed data processing (e.g., Spark, Dask, PySpark) and large-scale compute for AI workloads (experience)
• Experience with inference optimization frameworks (e.g. vLLM, TensorRT-LLM) (experience)
• Experience with LLM orchestration frameworks (e.g. LangChain, LangGraph) (experience)
• Contributions to or deep engagement with open-source developer tooling or ML frameworks (experience)
• Experience mentoring other engineers and raising a team’s engineering standards (experience)

Responsibilities

• In this role, you will architect and build core evaluation frameworks, systems, and tools that empower applied research and accelerate AI development. Your work will help researchers and developers close the gap between prototypes and production-grade capabilities, giving them a stable foundation to build on and enabling them iterate more quickly and produce more durable work. The tools you will develop will serve as the primary delivery mechanism for evaluation research innovations, distributing them to partner teams across the organization. This will involve deep collaboration with researchers, developers, engineers, and other users to understand their needs and ensure that solutions are easy to adopt and scalable. This is an opportunity to help build foundational systems and tools that translate cutting-edge methods and proven best practices into reliable, production-ready tools for development teams across ASE and partner organizations.

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