Gemini Enterprise Agent Engineer

We’re looking for an experienced AI engineer to lead the design, development, and governance of enterprise AI agents built on Gemini Enterprise and Gemini models.

You’ll own the full agent lifecycle, from architecture and grounding through deployment, evaluation, and governance, making sure our agents are accurate, safe, compliant, and trusted in production across the business.

What you’ll do

Build agents on Gemini Enterprise (formerly Agentspace)

• Design multi-agent solutions: architecture, orchestration, tool design, and multi-turn flows
• Configure grounding, enterprise search, and data connectors for accurate, properly scoped retrieval
• Integrate Gemini models via the Gemini API and Vertex AI, tuning prompts, context strategies, and function calling
• Productionize RAG pipelines and continuously evaluate agent quality (accuracy, relevance, latency, cost)

Lead AI governance and responsible agent operations

• Define access control, data permissions, usage policies, and approval workflows for production agents
• Build guardrails against hallucination, data leakage, prompt injection, and unauthorized access
• Set up monitoring, logging, and audit trails for agent behavior
• Partner with security, legal, and compliance on privacy, residency, and responsible-AI requirements
• Maintain lifecycle standards: build → evaluate → approve → monitor → retire

Collaborate and automate

• Turn business use cases into governed, production-ready agents with data science, AI engineering, and security teams
• Automate configuration, evaluation, and deployment with Python and Gemini Enterprise/Vertex AI SDKs
• Build dashboards that show agent inventory, usage, and governance status

What you bring (must have)

• 7+ years 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 agents on Gemini Enterprise (or Agentspace): agent design, grounding, enterprise search, connectors
• Strong experience with Gemini models (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
• Solid grounding in RAG, embeddings, vector search, and multi-agent orchestration
• Strong Python skills for automation, evaluation tooling, and API integrationWorking familiarity with GCP (IAM, Cloud Storage, basic networking)
• Nice to have

➕ Google Cloud certifications (Professional ML Engineer or Cloud Architect)
➕ Terraform, GKE, or CI/CD experience
➕ Observability experience (Cloud Monitoring, Prometheus, Grafana, Datadog)
➕ Familiarity with responsible-AI and model-risk frameworks
➕ Exposure to other GenAI platforms (OpenAI, Anthropic, open-source LLM stacks)

Pay: $6,000.00 - $15,000.00 per month

Benefits:

• Cell phone reimbursement
• Employee assistance programme
• Health insurance

Work Location: In person