Director, Data & AI/ML Platform Engineering

About Stitch Fix, Inc.

Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI.

About the Role

At Stitch Fix, data and AI are not supporting functions - they are the product. Every styling recommendation, merchandising decision, inventory bet, and client interaction is shaped by the platforms this role leads.

We are looking for a Director of Data & AI/ML Platform Engineering to lead the engineering organization responsible for three interconnected platform areas: the enterprise data platform that ingests, stores, and makes data queryable at scale; the machine learning platform that enables data scientists and engineers to build, train, and serve models in production; and the generative AI platform that provides the runtime, routing, and integration infrastructure for AI agents and LLM-powered applications across the company.

This is a product leadership role as much as it is an engineering leadership role. Your job is to understand what each of these user groups needs, set a compelling product vision for each platform area, and drive execution all the way through - from roadmap through adoption.

You will make the consequential architectural decisions that shape how the company builds with data and AI for years.

Why this role?

The platforms you would lead are not greenfield experiments. They are live production systems at a public company - real complexity, real stakes, and a clear strategic mandate to modernize and extend them.

• Meaningful scale: petabytes of data, thousands of daily pipelines, and a user base ranging from engineers and data scientists to business operators across every function
• Strategic mandate: the company's top strategic initiative is building the next generation of AI-powered personalization - this team builds the platform it runs on
• Real ownership: you will make consequential architectural decisions with real consequences, supported by a leadership team that trusts engineers to own their domain

Responsibilities

• Data infrastructure at scale. The systems that ingest, store, and make data accessible across the company - petabyte-scale lakehouse, event streaming, workflow orchestration, data governance, and the self-service tools that make this infrastructure usable without platform team involvement at every step.
• Machine learning platform. The infrastructure that enables data scientists and engineers to build, experiment, and serve models in production.