Required Skills and Experience:
· Mandatory:
· Proven AI transformation experience, including recent, personal delivery of production LLM applications and agents, preferably in regulated or security-sensitive environments.
· Deep AI architecture expertise spanning model selection, orchestration, data and context layers, identity, integration, and observability.
· Hands-on experience with multi-agent systems and Agent-to-Agent (A2A) interoperability, Model Context Protocol (MCP) servers and clients, and AI gateways for routing, access controls, guardrails, and cost governance.
· Strong practical knowledge of RAG, GraphRAG, context engineering, agent memory, and agent frameworks or SDKs; experience applying AI coding assistants and autonomous agents across the SDLC.
· Expertise in LLMOps, evaluation, regression testing, tracing, production monitoring, model adaptation, and inference optimization.
· Experience implementing defenses against prompt injection and tool misuse, human approval controls, and responsible AI governance.
· Hands-on experience with at least one major cloud AI platform—Azure AI Foundry, AWS Bedrock, or Google Vertex AI—and leading model-provider APIs.
· Strong executive communication, team leadership, and commercial judgment, with the ability to translate complex technology into compelling business value.
Success in This Role
· Secure, scalable AI adoption that moves beyond experimentation, delivers measurable engineering and business improvements, and maintains continuity from strategy and deal commitments through production execution.
AI Tools -
· Azure AI Foundry
· Agent365
· Copilot
· MS Purview
· Defender
