- Define and evolve enterprise AI architecture patterns for LLM integration, RAG, agentic workflows, and prompt orchestration.
- Design and build reusable AI components including connectors, agents, skill templates, and service APIs.
- Architect engineering controls for access management, data classification, prompt safety, and audit logging.
- Develop measurement approaches connecting AI usage to productivity, cost savings, and business value.
- Lead technical design for shared platforms supporting AI observability, model lifecycle management, and cost attribution.
- Mentor senior and mid-level engineers and drive cross-functional technical initiatives through production.
LLMMLOpsGenerative AI