AI Engineer; Agentic AI

· We are looking for a Gemini Enterprise Agent Engineer
** to lead the design, development, and governance of enterprise AI agents built on Gemini Enterprise and Gemini models.

· This role owns the full lifecycle of agent development — from architecture and grounding to deployment, evaluation, and ongoing governance — ensuring agents are accurate, safe, compliant, and trusted enough to run in production across the business.

· You'll be the go-to expert for building agents on Gemini Enterprise (agent design, orchestration, grounding, connectors) and for establishing the governance frameworks — access control, evaluation, auditing, and responsible‑AI guardrails — that keep those agents reliable at scale.

· Underlying cloud infrastructure runs on Google Cloud Platform (GCP), so working familiarity with GCP is helpful for collaborating with the platform team

• Gemini Enterprise Agent Development
  • oDesign, build, and own multi-agent solutions on Gemini Enterprise (formerly Agentspace) — agent architecture, orchestration, task/tool design, and multi-turn conversation flows.
  • oConfigure grounding, enterprise search, and data connectors so agents retrieve accurate, up-to-date, and properly-scoped information.
  • oIntegrate Gemini models (via the Gemini API and/or Vertex AI) into agents and downstream applications, tuning prompts, context strategies, and tool/function calling for reliability.
  • oDesign and product ionize RAG pipelines and retrieval strategies that feed agent grounding sources.
  • oContinuously evaluate and iterate on agent quality — accuracy, relevance, latency, and cost — using structured evaluation frameworks.
• AI Governance & Responsible Agent Operations
  • oDefine and implement governance frameworks for Gemini Enterprise agents: access control, data permissions, usage policies, and approval workflows for new agents going into production.
  • oBuild guardrails against hallucination, data leakage, prompt injection, and unauthorized data access across agents and connectors.
  • oEstablish monitoring, logging, and audit trails for agent behavior, including token usage, response quality, and policy violations.
  • oPartner with security, legal, and compliance stakeholders to ensure agents meet data privacy, residency, and responsible‑AI requirements.
  • oCreate and maintain documentation, review checklists, and lifecycle standards (build → evaluate → approve → monitor → retire) for enterprise agents.
  • oTrack Gemini model and Gemini Enterprise feature releases and assess their impact on existing agents and governance policies.
• Cross-Functional Collaboration & Automation
  • oWork closely with data science, AI engineering, security, and business teams to translate use cases into governed, production-ready agents.
  • oAutomate agent configuration, evaluation, and deployment workflows using Python and APIs/SDKs for Gemini Enterprise and Vertex AI.
  • oBuild internal tooling and dashboards to give stakeholders visibility into agent inventory, usage, and governance status.
  • oParticipate in code and design reviews, contributing to shared standards for agent development and governance.

• 7+ years of experience in AI/ML engineering, applied AI, or GenAI platform roles, with hands-on ownership of agent or LLM-application development.
• Direct, hands-on experience building and configuring agents on Gemini Enterprise (or Agentspace) — agent design, grounding, enterprise search, data connectors.
• Strong hands-on experience with Gemini models (via Gemini API or Vertex AI) — prompting, tool/function calling, context and RAG design.
• Practical experience implementing AI governance controls — access management, guardrails, evaluation frameworks, audit logging, and responsible‑AI policies for LLM/agent…