Senior AI Engineer – Forward Deployed, Agent Platform (REMOTE)

Position Purpose

• 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.

Key Responsibilities

• 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.

Working Conditions

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications

• 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 En