{"id":2529219,"url":"https://alion.io/job/gap-principal-engineer-agent-platform","title":"Principal Engineer, Agent Platform","company":{"id":12256,"name":"Gap Inc","domain":"gapinc.com","url":"https://alion.io/company/gap","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Folsom, United States","Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":272000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1093},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"BigQuery","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Google GKE","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Python","optional":false},{"name":"Vertex AI","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-06T00:00:00Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-15T17:22:58Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"About the Role\nWe are building the enterprise AI agent platform that teams across the company will use to create, deploy, govern, and operate AI-powered solutions at scale. As a Principal Engineer, you will help define the technical foundation for agent development across the organization, building the services, frameworks, and guardrails that make AI agents secure, reliable, observable, and easy to adopt.This is a hands-on engineering role focused on architecture, software design, and platform development. You will work across AI, distributed systems, cloud infrastructure, security, and governance to deliver a platform that enables product and engineering teams to move quickly while meeting enterprise standards for security, compliance, and operational excellence.\nWhat You'll Do\nDesign and build core platform services that enable enterprise AI agent development and operations\nDefine the architecture, engineering patterns, and technical standards for the AI agent platform\nDevelop and maintain a centralized model gateway for routing, governance, resiliency, and cost management\nBuild agent runtime capabilities that support long-running workflows, orchestration, and human-in-the-loop processes\nDesign secure identity, authorization, and policy enforcement mechanisms for agents and tools\nEstablish platform capabilities for context management, memory, retrieval, and data isolation\nCreate testing, evaluation, and release frameworks that ensure agent quality, safety, and performance\nImplement observability, auditability, and operational tooling for monitoring and troubleshooting agent behavior\nPartner with Security, Data Governance, and Cloud Infrastructure teams to define platform controls and guardrails\nMentor engineers, influence technical direction, and raise engineering standards across multiple teams\nWho You Are\nExtensive experience building and operating large-scale distributed systems in production\nStrong software engineering background with expert-level Python development skills\nHands-on experience delivering production LLM, generative AI, or agent-based solutions\nDeep understanding of agent architectures, orchestration patterns, and enterprise AI platforms\nExperienced with retrieval systems, embeddings, vector search, and context management strategies\nKnowledgeable in AI evaluation, testing methodologies, and quality assurance for non-deterministic systems\nProficient with Google Cloud services including Vertex AI, Gemini, GKE, Cloud Run, BigQuery, and Pub/Sub\nExperienced with cloud security, workload identity, OAuth, policy-as-code, and secure-by-design architectures\nStrong understanding of distributed system reliability patterns, including resiliency, retries, observability, and fault tolerance\nProven ability to influence technical direction, drive adoption of architectural standards, and lead through expertise rather than authority","description_format":"text","description_chars":2887,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Retail & Shop Systems","Apparel & Fashion Brands"],"lifecycle":[{"event":"open","at":"2026-10-14T12:34:02Z"}],"visa":[],"liveness":{"score":84,"band":"hot","label":"Hiring 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