Job Description
We are looking for an experienced Gemini Enterprise Agent Engineer to design, develop, deploy, and govern enterprise AI agents using Gemini Enterprise and Google Cloud technologies.
Key Responsibilities:
- Design and develop enterprise AI agents using Gemini Enterprise (Agentspace), including multi-agent orchestration and tool integration.
- Configure enterprise search, data connectors, grounding, and RAG pipelines.
- Integrate Gemini models through Gemini API and Vertex AI.
- Implement AI governance, access controls, security guardrails, and responsible AI policies.
- Establish agent evaluation frameworks, monitoring, audit logging, and performance optimization.
- Prevent hallucinations, prompt injection, data leakage, and unauthorized access.
- Automate agent development, evaluation, and deployment workflows using Python and APIs.
- Collaborate with AI, data, security, compliance, and business teams to deliver production-ready solutions.
Minimum Requirements:
- 7+ years of experience in AI/ML engineering, Applied AI, or Generative AI platforms.
- Hands-on experience with Gemini Enterprise (Agentspace), including agent design, grounding, enterprise search, and data connectors.
- Strong experience with Gemini models, Vertex AI, prompt engineering, tool/function calling, and RAG.
- Practical experience implementing AI governance, guardrails, evaluation frameworks, and audit logging.
- Strong Python programming and API integration skills.
- Understanding of embeddings, vector search, and multi-agent orchestration. Working knowledge of GCP, including IAM, Cloud Storage, and networking.
Good to Have:
- Google Cloud certifications in Machine Learning or Cloud Architecture.
- Experience with Terraform, Kubernetes/GKE, and CI/CD pipelines.
- Familiarity with Model Armor, Agent Development Kit (ADK), monitoring tools, and responsible AI frameworks.
- Exposure to other enterprise GenAI platforms such as OpenAI, Anthropic, or open-source LLMs.
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