Job Description
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.
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
AI & Machine Learning
Seniority Level:
Senior