Description

Define and govern the architectural foundations for the enterprise agent ecosystem. You will design agent-based integrations, registries, scoring infrastructure, and multi-agent orchestration platforms. This role requires technical leadership across engineering, product, data science, security, and cloud teams to ensure reliable, secure AI systems.

Responsibilities

• Design and oversee grounding patterns, RAG implementations, and multi-agent orchestration platforms.
• Establish and enforce enterprise architecture standards, patterns, and reference architectures for scalable AI.
• Collaborate with cross-functional teams to rapidly build AI-driven prototypes, proofs of concept, and production-ready solutions.
• Provide technical leadership to ensure scalable, observable, and high-performance distributed systems.
• Implement modern software development practices, API integrations, and identity management workflows.

Required Skills

• 10+ years of experience in cloud and distributed systems architecture.
• 7+ years designing enterprise AI/ML systems, with at least 1 year of hands-on experience in GenAI or agentic workflows.
• Expertise with agentic frameworks: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, Agent SDK, or OpenAI SDK.
• Proficiency with MCP (Model Context Protocol) and LLM-based integrations.
• Strong experience with Azure and GCP, including Kubernetes, containerization, and CI/CD pipelines.
• Deep understanding of scalability, reliability, observability, and network security in cloud environments.

Preferred Skills

• Experience with multi-agent systems and complex orchestration logic.
• Background in defining enterprise-wide AI governance and evaluation infrastructure.

Key Skills

Education

Any Graduate