Agentic AI Expert

Deep expertise in agentic AI systems and LLM-driven orchestration frameworks Strong understanding of reasoning models and agent reasoning loops Proven experience evaluating production-grade AI platforms and workflows Ability to work independently and provide architectural-level recommendations Strong communication skills to collaborate with distributed, cross-functional teams Hands-on experience with LangGraph or comparable agent orchestration frameworks (highly desirable) Strong understanding of MCP (Model Context Protocol) and managed identity patterns (highly desirable) Experience designing agents with memory, retries, observability, and safety controls (highly desirable) Demonstrated ability to build agents that run natively inside Kubernetes pods (highly desirable) Familiarity with CI/CD-driven agent execution and code automation workflows (highly desirable)

Evaluate and improve Broadcom’s LangGraph-based workflow and reasoning engine Review, refine, and optimize agent libraries, templates, and orchestration patterns Assess and enhance agent autonomy, retries, memory usage, and context management Analyze and improve agent identity, observability, safety, and governance mechanisms Support agent-to-agent (A2A) communication patterns and execution workflows Collaborate with platform teams to ensure scalable, reliable agent execution within Kubernetes pods Provide technical guidance and best practices for expanding the agent ecosystem and roadmap