Description

Define and govern the architectural foundations for the enterprise agent ecosystem. Design agent-based integrations, registries, evaluation infrastructure, grounding patterns, and multi-agent orchestration platforms.

Responsibilities

• Establish and enforce enterprise architecture standards, patterns, and reference architectures for scalable AI platforms.
• Provide technical leadership across engineering, product, data science, security, and cloud teams.
• Collaborate with cross-functional teams to build AI-driven prototypes, proofs of concept, and production-ready solutions.
• Oversee the design and implementation of reliable, secure, and high-performance AI systems.

Required Skills

• 10+ years of experience in cloud and distributed systems architecture, focusing on scalability, reliability, observability, and performance.
• 7+ years designing enterprise AI/ML systems, including 1+ years hands-on with GenAI, agentic workflows, RAG, LLM integrations, or multi-agent systems.
• Strong expertise with agentic frameworks: MCP, LangChain, LangGraph, LlamaIndex, autogen, crewai, Agent SDK, OpenAI SDK.
• Proficiency with Azure and GCP, including Kubernetes, containerization, identity management, networking, CI/CD, and API platforms.
• Hands-on experience with modern software development practices, API integrations, and enterprise system workflows.

Key Skills

Education

Any Graduate