Forward Deployed AI Engineer

Requirements

• 5+ years of software engineering, strong Python
• Production experience with LLM applications: tool calling, structured output, prompt and context design, evaluation, guardrails
• Hands-on Google Cloud. Vertex AI and ADK preferred, solid GCP serverless experience accepted
• Google Workspace APIs in production (Calendar, Gmail, Sheets) and Apps Script
• OAuth 2.0, service accounts, domain-wide delegation, least-privilege access
• Integration engineering: webhooks, event-driven flows, retries, idempotency, logging and alerting
• Builds deterministic workflows first and adds the model where it pays off
• Upper-intermediate or better spoken and written English, comfortable running calls with business users alone
• Careful with sensitive data and strict confidentiality rules

Nice-to-Have

• Vertex AI Agent Engine, Memory Bank, Gen AI evaluation service
• Slack apps (Bolt, Block Kit, slash commands, interactive approvals)
• Calendar scheduling logic: availability search, constraints, time zones, recurring events
• Admin SDK Reports API or other Workspace audit tooling
• MCP servers and clients, A2A
• Claude or Gemini models in production, model routing
• Financial services, private equity or executive assistant workflows
• Experience teaching non-technical users

Responsibilities

• Own delivery of agents and automations from the first workflow walkthrough to production and support
• Turn documented client processes into a design: which steps are code, which use a model, where a human approves
• Build agents in ADK, deploy on Vertex AI Agent Engine or Cloud Run, connect to Google Workspace and Slack
• Set up evaluation and regression checks so each agent is retested when a model version changes
• Run a short daily or near-daily sync with the client contact during her morning hours
• Write short runbooks and walk client users through how each solution worksKeep monthly work plans and status current for the architect and account lead
• Follow the client confidentiality policy: approved tools only, no AI note takers, no client data outside approved locations

About project

The client is a US-based financial services firm that runs fully on Google Workspace and Slack. The project builds AI agents and automations for the firm’s internal operations: scheduling, OKR tracking, email handling, and team requests across the executive office and operations teams. The focus is on reliable, production-grade solutions. Deterministic logic comes first, and LLMs are used where they add real value, backed by evaluation and human oversight.