• Lead the 0→1 buildout and 1→n scaling of AI capabilities at Optimal Dynamics; set direction and establish engineering standards. • Own RAG initiatives end-to-end from problem framing and data readiness through prototyping, iteration, and production launch. • Establish foundational components and practices for document processing, indexing, retrieval, orchestration, and evaluation. • Select tools and approaches that balance quality, cost, and speed. • Build reliable services and APIs that are observable, secure, and designed for scale in a cloud environment. • Define success metrics (quality, latency, cost, safety) and drive continuous improvement via experimentation and data-driven decisions. • Create durable team assets (playbooks, test harnesses, checklists, and documentation) to make RAG development repeatable across products. • Collaborate cross-functionally with Product, Data/ML, Engineering, and GTM to translate ambiguous needs into shippable capabilities with clear business impact. • Mentor teammates and contribute to a strong engineering culture around AI systems and responsible deployment. • Make key architecture and tooling choices and evolve them as the team learns.