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# Senior AI Engineer - Forward Deployed, Agent Platform (REMOTE)

- **Company:** Home Depot USA Inc.
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $100,000 - $180,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Clean Code Principles, Microsoft Access, A/B Testing, Artificial Intelligence, Computing Platforms, Confluence, JIRA, Audit Trail, BigQuery, Software as a Service, Nvidia CUDA, Continuous Integration, Data Masking, Data Stores, Identity and Access Management, Python (Programming Language), Knowledge-Based Systems, Machine Learning, OAuth, Role-Based Access Control, OpenAI, Prometheus, Gemini Enterprise (Agent Platform), Salesforce.Com, Microsoft SharePoint, Software Engineering, SQL Databases, Systems Integration, TypeScript, Data Logging, Apex Code, Feature Store, Enterprise Software Applications, ReactJS, Retrieval-Augmented Generation, System Availability, Large Language Models, Grafana, Prompt Engineering, Agentic-AI, Vertex AI Vector Search, Fastapi, Slack, CrewAI, Low-code, AutoGen, Claude, Google Gemini, Terraform, Network Server, Human in the Loop, Docker, Servicenow, Microservices
- **Published:** November 5, 2026
- **Apply:** https://www.atlantacareerpath.com/job.asp?id=3496632568&tx=JT10092UYD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Must be eighteen years of age or older.
 * Must be legally permitted to work in the United States., * 6+ yrs shipping/operating production Python services (FastAPI, async microservices, REST)
 * Multi-step agent orchestration (Google ADK, LangGraph, CrewAI, AutoGen, or equivalent) & LLM APIs (Gemini, Claude, OpenAI)
 * Systematic prompt engineering, structured outputs, context optimization & evaluation
 * Enterprise SaaS & MCP integration + auth boundaries (OAuth2, SSO, service accounts, delegated user, RBAC)
 * RAG, knowledge ingestion & search (Vertex AI Search / Gemini Enterprise Data Stores, access-scoped retrieval)
 * Agent evaluation harnesses, golden datasets & HA/defensive coding practices
 * GCP (Vertex AI, Cloud Run, BigQuery), analytical SQL, CI/CD, and observability (Grafana, Prometheus, OpenTelemetry), * The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education:

 * No additional education

Minimum Years of Work Experience:

 * 2

Preferred Years of Work Experience:

 * No additional years of experience, * Global Perspective
 * Manages Ambiguity
 * Nimble Learning
 * Self-Development
 * Collaborates
 * Cultivates Innovation
 * Situational Adaptability
 * Communicates Effectively
 * Drives Results
 * Interpersonal Savvy, Benefits 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 .

## Description

* Embed 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.
 * Educate & 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.
 * Drive 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.
 * Explicit 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.

Responsibilities:

 * Embed & 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.
 * Build & 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.
 * Engineer 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.
 * Establish Reusable Evaluation Harnesses: Build workflow-level golden datasets, prompt/agent evaluations, and automated regression suites so business owners have an objective pass/fail gate.
 * Templatize & 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.
 * Review 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.
 * Execute Ownership Handoff & Enablement: Author runbooks and enablement materials, verify receiving-owner readiness, and cleanly transfer day-to-day operations to the vertical.
 * Feed Platform Architecture: Convert recurring vertical needs into scoped backlog items for the core APEX platform (Gateway/Registry, Model Armor guardrails, observability, and lifecycle management).
 * Enable 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., * 70% 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
 * 10% 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
 * 20% 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

Direct Manager/Direct Reports:

 * This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager
 * This Position has 0 Direct Reports

Travel Requirements:

 * Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:

 * Most 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., * Forward-deployed execution: cross-functional collaboration across skill levels, code/prompt review, enablement docs & handoff
 * 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.
 * Direct hands-on experience with Gemini Enterprise, Vertex AI Search / Data Stores, Google ADK, and MCP / FastMCP
 * Prior Forward Deployed, Solutions, or Embedded Platform Engineer experience
 * HITL approval workflows, write-action safety controls & immutable audit trails
 * Responsible AI & safety guardrails in prod (Model Armor, prompt-injection defense, bias/hallucination mitigation, PII redaction)
 * A/B testing, graph/connected knowledge systems, Terraform/HCL, Docker/GKE, and TypeScript/React/JS for UI/Canvas surfaces
 * Retail, eCommerce, supply chain, store ops, or finance domain background