hands-on agentic AI workflows, mentor engineering teams, and establish enterprise standards for AI-assisted software development, spanning the entire Software Development Life Cycle (SDLC). Key Responsibilities Agentic AI Engineering: Build and run agent workflows, handle model selection, prompt/harness engineering, agent-tool integration, and manage reusable skills … instructions. SDLC Integration: Apply AI across the full software lifecycle, including test generation, code review augmentation, documentation, legacy comprehension, and modernisation. AI Tooling & Ecosystem: Leverage and integrate AI coding and agent tooling such as Claude Code, GitHub Copilot, Codex, Kiro, and MCP server development. Standards & Governance: Define standards, guardrails ...