Principal Engineer, Agentic Applications

RiseMe; Folsom (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Gap Inc. seeks a senior engineering leader to bridge creative design, product creation, and the global supply chain through AI/ML-backed multi-agent workflows. You will build and ship agentic systems that transform mood boards, tech packs, fabric specs, and vendor data into live production decisions.

As a hands-on senior leader, you will own technical standards, agent data designs, and the reference architecture for our agent framework while co-owning the product-to-market journey.

Qualifications

• 12+ years in software/data/ML engineering, with hands-on experience building and shipping production AI/ML systems.
• Experience setting technical standards in a large enterprise.
• Production AI systems with LLM-based agents or multi-agent orchestration preferred.
• Willingness to write and review code alongside architecture work.

Responsibilities

• Own Technical Standards. Set and enforce engineering standards, contracts, and integration patterns for agentic solutions across design tools, PLM, vendor management, procurement, and more.
• Architect Agent-Ready Data. Design data strategies for ingesting, embedding, and exposing AI-ready data products.
• Co-Own the Agentic Reference Architecture. Define the agent harness, orchestrator patterns, and tool contracts with model-agnostic stance.
• Lead Complex Product-to-Market Agent Workflows. Build and deploy multi-agent systems for design, development, and sourcing workflows.
• Partner on Guardrails & Governance. Drive FinOps and安全 by collaborating with Trust, Security, and Governance teams.
• Elevate the Engineering Bar. Mentor engineers and represent engineering in architecture reviews.

Job description

About the Role

In 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 Do

• Own 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 opinion

• Architect 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 loops

• Co-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 agnostic

• Lead 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 failures

• Elevate 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 Are

• 12+ 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 diagrams

• Staff/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 them

• Production 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 conceptually

• Comfortable with conflict. Across engineering, sciences, platform, senior leadership, and security, you stand behind core design principles and rigor