Description

You will define and govern the architectural foundations for the organization's enterprise agent ecosystem, ensuring reliable, secure, and high-performance AI systems.

This role is hybrid.

Responsibilities

• Design and oversee agent-based integrations, registries, scoring/evaluation infrastructure, grounding patterns, and multi-agent orchestration platforms.
• Provide technical leadership across engineering, product, data science, security, and cloud teams to establish enterprise architecture standards and reference architectures.
• Collaborate with cross-functional teams to rapidly build AI-driven prototypes, proofs of concept, and production-ready solutions.
• Ensure scalability, reliability, observability, and performance of distributed systems and AI platforms.

Required Skills

• 10+ years of experience in cloud and distributed systems architecture.
• 7+ years designing enterprise AI/ML systems, including at least 1 year of hands-on experience with GenAI, agentic workflows, RAG, LLM-based integrations, or multi-agent systems.
• Strong expertise with agentic frameworks and tooling such as MCP, LangChain, LangGraph, LlamaIndex, Autogen, CrewAI, Agent SDK, or OpenAI SDK.
• Proficiency with cloud platforms like 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.
• Any Graduate.

Preferred Skills

• Experience establishing and enforcing enterprise architecture standards for scalable AI platforms.
• Proven track record of delivering production-ready AI solutions in a cross-functional environment.

Key Skills

Education

Any Graduate