Job Title: Agentic AI Architect
Location: Remote
Contract: 6-9+ months.
Experience: 12+ years
Job Description:
Mandatory Skills:- Gemini Enterprise, Vertex AI, ADK, Agent Engine, A2A, MCP, Model Garden
Role Summary
Owns the end-to-end AI agent architecture for Intel& Agent Factory. Defines reusable patterns,
orchestration standards, model selection, tool integration, security, and technical governance, ensuring
modularity, scalability, and reuse across enterprise functions.
Key Responsibilities
• Design multi-agent reference architectures using Gemini Enterprise, ADK, Agent Engine, A2A,
and MCP.
• Define agent blueprints, composable design standards, and the Intel Agent Library structure.
• Establish orchestration, memory, RAG, and tool-invocation strategy.
• Guide model selection (Gemini Pro / Flash / Flash-Lite) balancing cost, latency, and quality.
• Own security architecture (IAM, VPC-SC, Model Armor) and observability standards.
• Review and approve all agent-level technical designs and integration approaches.
Mandatory (Must-Have) Skills
• Deep expertise in Gemini Enterprise, Vertex AI, ADK, Agent Engine, A2A, MCP, Model Garden.
• Strong RAG, vector DB, embeddings, and knowledge-graph design.
• Secure enterprise-scale AI platform architecture (IAM, VPC-SC, DLP, guardrails).
• Microservices, containers (GKE/Cloud Run), API design.
Preferred (Good-to-Have) Skills
• Multi-agent systems and agentic orchestration patterns.
• Cost/latency optimization and model tiering.
• Prior GSI / large enterprise AI transformation experience.
Experience & Certifications
• 12+ years IT with 3+ years in AI/GenAI/agentic architecture.
• Google Cloud Professional Architect certification strongly preferred.
• Must be able to work onsite in the USA.
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