Stitch Fix is looking to evolve its modern data stack to support the next wave of AI/ML-powered products, analytics, and knowledge systems. The goal is to make the data platform easier to scale, easier to find information in, and more reliable as AI is integrated into workflows, ultimately supporting smarter automation and delivering better insights.
Requirements
- You have 8+ years of experience building cloud-scale data infrastructure or ML platforms
- You've contributed to AI-focused systems such as LLM APIs, RAG/GraphRAG, vector search, or knowledge graphs
- You've worked with vector and graph databases to support intelligent querying and semantic discovery
- You're hands-on with Spark, SQL, and Python and/or Scala with strong experience building scalable APIs and services
- You understand streaming systems such as Kafka or Flink and how to design for real-time insights
- You have experience with orchestration systems, CI/CD, and production monitoring
- You're interested in defining data product standards, governance-by-design, and AI observability metrics
Responsibilities
- Evolve our core data stack (Spark, Trino, Iceberg, Kafka, Flink) to meet the scale and latency demands of AI workloads
- Define and implement observability, lineage, and access standards for our data products and AI applications
- Support critical data pipelines while creating abstractions that simplify end-user interactions
- Unify workflows from data ingestion to model serving, ensuring a shared foundation for feature stores, ML observability, and semantic modeling
- Design and build foundational AI data capabilities supporting LLM orchestration, retrieval-augmented generation (RAG/GraphRAG), semantic data layers, and vectorized search
- Work with teams to build well-documented, AI-friendly datasets that power analytics, personalization, and better business decisions
Other
- You thrive in cross-functional, collaborative environments and navigate evolving priorities effectively
- You're detail-oriented, curious, and passionate about building infrastructure people love to use
- We cultivate a community of diverse perspectives— all voices are heard and valued.
- We win as a team, commit to our work, and celebrate grit together because we value strong relationships.
- We are the owners of our work and are energized by solving problems through a growth mindset lens.
