Architect analytical and customer-centric platforms that are scalable, secure, maintainable, and interoperable across a large ecosystem of systems, Stay deeply hands-on, contributing roughly 40 to 60 percent to development across all phases of the software lifecycle, with the remaining time spent on architecture, technical strategy, cross-team alignment, and raising engineering quality. Hands-on experience designing and shipping AI/ML capabilities in production, ideally including LLM-based or agentic systems (multi-agent orchestration, retrieval-augmented generation, prompt and context engineering, agent memory, evaluation, and guardrails).