Hands-on experience with modern AI/LLM development, including: Context engineering - designing what informs the model's context window, including agentic retrieval and search, memory architectures, grounding in enterprise data, and structured outputs; Agentic system design - agent loop engineering, multi-agent and sub-agent orchestration, and tool/function calling; Context window management and token budgeting, including cost and latency optimization for production workloads; Evaluation of AI system quality, reliability, and safety. Responsibilities: Design, build, and deploy AI-powered capabilities across the SDLC, including: Spec Driven Development workflows that support the translation of well-formed specifications into secure, verifiable implementations; Assurance of AI-generated code - guardrails, policy enforcement, and verification for code produced by AI assistants and agents; SDLC skills and agent tooling - developer-assist skills as well as verification skills that perform automated security checks (design review, dependency and supply-chain analysis, static/dynamic analysis orchestration, release audit support).