Description

You will design and govern the architecture for agentic systems using GCP Vertex AI.

Responsibilities

• Define GCP Vertex AI and Agentspace architecture standards for agent development, grounding, and memory.
• Orchestrate and design Agent-to-Agent (A2A) coordination between agents and enterprise systems like SAP, Salesforce, or ServiceNow.
• Develop Context Engineering patterns to ensure reliable grounding for generative AI systems.
• Establish processes for testing, observability, safety, and control within GenAI deployments.
• Lead enterprise governance, LLMOps, AgentOps, and lifecycle management for AI solutions.

Required Skills

• 14+ years of experience in AI/ML, cloud, platform engineering, or enterprise architecture.
• 3+ years hands-on experience with GCP Vertex AI, including Agentspace, Agent Builder, Vector Search, or Search & Conversation, and ability to describe a built solution.
• 2+ years building Generative AI applications, such as AI assistants or retrieval-based systems.
• 5+ years strong Python development experience building production backend services and APIs.
• 3+ years of cloud deployment experience using GCP services like Cloud Run, Cloud Functions, or Kubernetes.
• Practical integration experience with SAP, Salesforce, or ServiceNow, detailing a real integration scenario.
• 1–2 years operationalizing AI systems, covering prompt management, error handling, or performance monitoring.
• Experience designing enterprise-grade AI or agentic systems with AgentOps exposure.

Key Skills

Education

Any Gradute