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About Gap Inc.At Gap Inc., we create culture as much as we create clothes. Our ambition is to become a high-performing house of iconic American brands that shape culture.Our portfolio—Old Navy, Gap, Banana Republic, and Athleta—each brings a distinct point of view to how we show up in the world and serve our customers.Old Navy democratizes style with quality and value for all. Gap champions originality through essential pieces that celebrate individuality. Banana Republic is rooted in a spirit of discovery, creating modern pieces inspired by craftsmanship and travel. Athleta champions the Power of She through confidence, strength, and movement.We’re driven by a shared purpose: to bridge gaps—between people, perspectives, and possibilities—to create a better world.We’re building a team that performs at a high level—people who think boldly, take ownership, and turn ideas into impact. If you’re ready to learn fast and help shape what’s next, you’ll fit right in.About the roleIn this role, you will bridge creative design, product creation, and the global supply chain for Gap Inc. This is not a research role — you will build and ship AI/ML-backed multi-agent workflows that turn structured & unstructured data, mood boards, tech packs, fabric specs, vendor collaboration, etc. into live, sometimes autonomous, production decisions.As a senior, hands-on engineering leader, you will direct the technical standards of the agentic systems that allow our business to operate at AI-native speed and scale. You will drive this transformation while owning the agentic application and AI-ready data designs, and co-owning the reference architecture and agent framework for our product-to-market journey.What you'll doOwn Technical Standards. Set and enforce engineering standards, contracts, and integration patterns — including interoperability protocols such as MCP/A2A — for agentic solutions across digital apparel design tools, PLM systems, vendor management, procurement, compliance, logistics, etc. Set the engineering definition-of-done, establishing system quality through evaluation gates (LLM-as-judge, golden datasets) rather than subjective opinionArchitect Agent-Ready Data. Shape the data strategy for how structured and unstructured design and sourcing assets are ingested, embedded, structured, and exposed as reliable, reusable AI-ready data products — that provide features for sciences and ontology + context for multi-agent loopsCo-Own the Agentic Reference Architecture. With peer AI/ML platform teams, design the agent harness (including trust frameworks), core orchestrator pattern, semantic/business-context layers, and the tool contracts for the ML and data platforms while being model agnosticLead Complex Product-to-Market Agent Workflows. Build and deploy multi-agent systems that orchestrate tool-use and multi-step reasoning across Design, Development, and Sourcing — auto-generating BOMs, negotiating RFPs, allocating materials, etc.Partner on Guardrails & Governance. Drive FinOps including cost-aware routing across Vertex Model Garden based on latency, cost, and capability, backed by real data. Collaborate closely with Trust, Security, and Governance teams to ensure agents ship safe, grounded, entitlement-aware, and gated against non-deterministic failuresElevate the Engineering Bar. Mentor data and agent engineers across delivery pods and vendor-augmented teams by building alongside them, not just reviewing PRs; represent agentic engineering in architecture reviews with senior technology leadership Who you are12+ years, hands-on. In software/data/ML engineering, with recent experience building and shipping production AI/ML systems — ideally LLM-based agents or multi-agent orchestration, not just classical ML pipelines. You're still writing and reviewing code by choice, not solely reviewing architecture diagramsStaff/Principal/Architect track record. At a large, complex enterprise, you've set technical standards that other engineering teams were expected to follow, not just proposed themProduction agent and cloud AI experience. Comfort with orchestration patterns (e.g., LangGraph, custom orchestrators, or equivalent), and hands-on depth with at least one major cloud AI stack (GCP/Vertex preferred). You've built or owned LLM-as-judge pipelines, golden datasets, or comparable quality gates for a production AI system, not just discussed them conceptuallyComfortable with conflict. Across engineering, sciences, platform, senior leadership, and security, you stand behind core design principles and rigorSalary Range: $209,700.00 - $272,600.00Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.Benefits at Gap Inc.Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees.One of the most competitive Paid Time Off plans in the industry.*Employees can take up to five “on the clock” hours each month to volunteer at a charity of their choice.*Extensive 401(k) plan with company matching for contributions up to four percent of an employee’s base pay.*Employee stock purchase plan.*Medical, dental, vision and life insurance.*See more of the benefits we offer.*For eligible employees

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