Main Activities:
• Define enterprise AI platform architecture and roadmap.
• Design, build and operate AI-native CI/CD platforms.
• Implement secure-by-design AI controls and governance.
• Define reliability, observability, resilience and FinOps practices.
• Lead architecture reviews and developer enablement programs.
• Provide technical leadership across engineering teams.
Knowledge/Skill Requirements:
• 7+ years of software, platform, or cloud engineering experience, with 3+ years in AI/ML platforms or agentic AI systems.
• Deep hands-on expertise with Azure (AKS, networking, private endpoints, identity, Key Vault) and Azure AI Foundry or equivalent AI platforms.
• Proven experience building CI/CD pipelines for ML/LLM workloads (model, prompt, and agent lifecycle management).
• Strong background in distributed systems, container orchestration (Kubernetes), and API/SDK design.
• Experience with agent frameworks (e.g., Semantic Kernel, LangChain, AutoGen) and orchestration patterns (memory, tools, planning).
• Solid understanding of LLM inference optimization, model routing, evaluation, and observability.
• Track record of establishing platform standards, paved paths, and developer enablement at scale.
• Excellent collaboration and communication skills across engineering, security, risk, and business stakeholders.
Preferred Qualifications
• Prior experience in regulated industries (financial services, banking, insurance).
• Familiarity with Microsoft Fabric, Power Platform, Copilot, and Copilot Studio integrations.
• Experience with FinOps for AI workloads including cost attribution, token accounting, and model economics.
• Background in Responsible AI, model governance, and evaluation frameworks.
• Contributions to open-source AI/agent platform projects.