{"id":192655,"url":"https://alion.io/job/homedepot-senior-machine-learning-engineer-generative-ai-remote","title":"Senior AI Engineer – Forward Deployed, Agent Platform (REMOTE)","company":{"id":13463,"name":"The Home Depot","domain":"homedepot.com","url":"https://alion.io/company/homedepot","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":96,"ghost_share":0,"stale_share":0.74,"repost_share":0.01,"time_to_fill_p50_days":36,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":100000,"max":180000,"currency":"USD","period":"year","gross":null,"usd_annual":180000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Confluence","optional":false},{"name":"CUDA","optional":false},{"name":"FastAPI","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gemini","optional":false},{"name":"Google ADK","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"IAM","optional":false},{"name":"Jira","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"ServiceNow","optional":false},{"name":"SharePoint","optional":false},{"name":"Slack","optional":false},{"name":"A/B Testing","optional":true},{"name":"AutoGen","optional":true},{"name":"CI/CD","optional":true},{"name":"Claude","optional":true},{"name":"CrewAI","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Google Cloud Run","optional":true},{"name":"Google GKE","optional":true},{"name":"Grafana","optional":true},{"name":"Hallucination","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Least Privilege","optional":true},{"name":"LLM","optional":true},{"name":"OpenAI","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true},{"name":"React.js","optional":true},{"name":"SQL","optional":true},{"name":"Structured Outputs","optional":true},{"name":"Terraform","optional":true},{"name":"TypeScript","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-09-02T21:14:14Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-03T23:34:20Z","board_verified":true,"closed_at":null,"days_open":62,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":62},"description":"With a career at The Home Depot, you can be yourself and also be part of something bigger.\nPosition Purpose:\nEmbed with THD Business Verticals: Partner directly with Finance, Marketing, Supply Chain, Online, Store Ops, HR, and Legal/Risk, etc., to turn ambiguous operational processes into production-ready, enterprise-governed AI agents.\nEducate & Enable: Teach verticals what surfaces they can deploy on (Gemini Enterprise, Google ADK, Skills, Agent Designer, MCP servers, Canvas, Agent Gateway/Registry) and how to manage and evolve their agents. Consult business on technical approaches to build agents.\nDrive Adoption & Reuse: Grow Gemini Enterprise adoption across the enterprise - team agents, individual Sparks, and a marketplace of reusable enterprise agents, Skills and tools. Treat every engagement as supply for the marketplace and actively promote reuse so teams compose existing assets before building new ones.\nExplicit Scope Guardrail: Foundation models are consumed as managed services-no pre-training/fine-tuning models, no GPU/CUDA kernel work, and no classical feature stores or model registries.\nResponsibilities:\nEmbed & Discover Workflows: Sit with non-technical business partners to elicit requirements, define negative scope (\"what the agent must never do\"), and lock in acceptance criteria before coding.\nBuild & Deploy Production Agents: Ship end-to-end multi-step agents and conversational assistants in Python (FastAPI), Google ADK, and Gemini Enterprise, including Human-in-the-Loop (HITL) confirmation gates for write actions.\nEngineer Enterprise Integrations & MCP Servers: Build resilient MCP servers and REST integrations for enterprise systems (e.g. Jira, Confluence, SharePoint/M365, Slack, ServiceNow, Salesforce, etc.) with strict OAuth/IAM boundaries, idempotency, retries, and High Availability patterns; publish them as reusable assets in the enterprise marketplace.\nEstablish Reusable Evaluation Harnesses: Build workflow-level golden datasets, prompt/agent evaluations, and automated regression suites so business owners have an objective pass/fail gate.\nTemplatize & Build the Paved Road: Extract reusable templates, Skills, and packaging standards from every build so the second vertical build takes ≤60% of the effort of the first.\nReview Submissions & Govern Quality: Review partner-submitted agent code, company Skills, and prompt implementations for the Agent Sharing & Registry workflow against engineering, security, and Responsible AI standards;curate the marketplace so published agents, Skills and tools are discoverable, documented and trusted.\nExecute Ownership Handoff & Enablement: Author runbooks and enablement materials, verify receiving-owner readiness, and cleanly transfer day-to-day operations to the vertical.\nFeed Platform Architecture: Convert recurring vertical needs into scoped backlog items for the core APEX platform (Gateway/Registry, Model Armor guardrails, observability, and lifecycle management).\nEnable Builders & Grow Adoption: Support product to run technical workshops, office hours; review low-code agents built by business teams; maintain documentation and a pattern library; and use usage data and feedback to improve adoption and the platform.\nKey Responsibilities:\n70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do \"destructive testing\" to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively\n10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations\n20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality\nDirect Manager/Direct Reports:\nThis Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager\nThis Position has 0 Direct Reports\nTravel Requirements:\nTypically requires overnight travel 5% to 20% of the time.\nPhysical Requirements:\nMost of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.\nWorking Conditions:\nLocated in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.\nMinimum Qualifications:\nMust be eighteen years of age or older.\nMust be legally permitted to work in the United States.\nPreferred Qualifications:\n 6+ yrs shipping/operating production Python services (FastAPI, async microservices, REST)\n Multi-step agent orchestration (Google ADK, LangGraph, CrewAI, AutoGen, or equivalent) & LLM APIs (Gemini, Claude, OpenAI)\nSystematic prompt engineering, structured outputs, context optimization & evaluation\n Enterprise SaaS & MCP integration + auth boundaries (OAuth2, SSO, service accounts, delegated user, RBAC)\n RAG, knowledge ingestion & search (Vertex AI Search / Gemini Enterprise Data Stores, access-scoped retrieval)\nAgent evaluation harnesses, golden datasets & HA/defensive coding practices\n GCP (Vertex AI, Cloud Run, BigQuery), analytical SQL, CI/CD, and observability (Grafana, Prometheus, OpenTelemetry)\nForward-deployed execution: cross-functional collaboration across skill levels, code/prompt review, enablement docs & handoff\n Customer-facing delivery & communication: demonstrated experience working with nontechnical stakeholders, comfort with ambiguity, and presenting technical tradeoffs to executives (assessed in the interview via a mock discovery session). •Security & Responsible AI fundamentals for agents that take write actions: PII handling, HITL approvals, audit trails, and least-privilege access.\nDirect hands-on experience with Gemini Enterprise, Vertex AI Search / Data Stores, Google ADK, and MCP / FastMCP\nPrior Forward Deployed, Solutions, or Embedded Platform Engineer experience\nHITL approval workflows, write-action safety controls & immutable audit trails\nResponsible AI & safety guardrails in prod (Model Armor, prompt-injection defense, bias/hallucination mitigation, PII redaction)\nA/B testing, graph/connected knowledge systems, Terraform/HCL, Docker/GKE, and TypeScript/React/JS for UI/Canvas surfaces\nRetail, eCommerce, supply chain, store ops, or finance domain background\nMinimum Education:\nThe knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.\nPreferred Education:\nNo additional education\nMinimum Years of Work Experience:\n2\nPreferred Years of Work Experience:\nNo additional years of experience\nMinimum Leadership Experience:\nNone\nPreferred Leadership Experience:\nNone\nCertifications:\nNone\nCompetencies:\nGlobal Perspective\nManages Ambiguity\nNimble Learning\nSelf-Development\nCollaborates\nCultivates Innovation\nSituational Adaptability\nCommunicates Effectively\nDrives Results\nInterpersonal Savvy\nBenefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.\nFor California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:\nThe pay range for this position is between $100,000.00 - $180,000.00","description_format":"text","description_chars":8362,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"high_school","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Tools & DIY Supplies","Kitchens, Bathrooms & Home Improvement","Building Materials"],"lifecycle":[{"event":"open","at":"2026-09-02T21:14:14Z"},{"event":"close","at":"2026-10-18T12:05:32Z"},{"event":"reopen","at":"2026-11-03T17:13:28Z"}],"visa":[],"liveness":{"score":24,"band":"cold","label":"Long shot","p_open":1,"p_active":0.68,"p_room":0.36,"age_days":62,"expected_fill_days":36,"reasons":["conf:4","win:tail","crowd:brand"],"computed_at":"2026-11-04T04:24:06Z"},"pay":{"stated_usd_annual":180000,"is_top_pay":false},"html_url":"https://alion.io/job/homedepot-senior-machine-learning-engineer-generative-ai-remote","json_url":"https://alion.io/job/homedepot-senior-machine-learning-engineer-generative-ai-remote.json","meta":{"generated_at":"2026-11-04T04:24:06Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":6850,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-05T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":13463},"rest":"https://alion.io/mcp/rest/get_company?id=13463"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhomedepot-senior-machine-learning-engineer-generative-ai-remote"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fhomedepot-senior-machine-learning-engineer-generative-ai-remote"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fhomedepot-senior-machine-learning-engineer-generative-ai-remote"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/homedepot-senior-machine-learning-engineer-generative-ai-remote\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhomedepot-senior-machine-learning-engineer-generative-ai-remote"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":192655}},{"tool":"search_jobs","arguments":{"company":"homedepot.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":192655},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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