• Build and evolve our Conversation Engine powering pre-drafted email, chat, and voice responses, including conversation state, memory, and high-quality response generation. • Own the RAG pipeline end-to-end : document ingestion, chunking strategies, embeddings, indexing, retrieval (hybrid/vector), reranking, and grounded response generation. • Implement AI Tooling / function calling to connect LLM workflows to internal systems (e.g., account lookup, case context retrieval, knowledge base queries ) with strong validation and safe execution patterns. • Design evaluation and quality systems for AI features: offline eval harnesses, golden datasets, human feedback loops, monitoring for hallucinations/grounding, and regression prevention. • Collaborate with cross-functional teams to define, design, and ship new features. • Work closely with business stakeholders and customers to translate requirements into technical specifications and documentation. • Mentor and support engineering team members, promoting team efficiency and growth. • Troubleshoot and debug complex issues, ensuring timely resolution and platform stability. • Optimize application performance, reliability, and scalability, and uphold high standards for clean, maintainable code. • Identify and proactively address technical debt and performance bottlenecks to drive iterative product improvement.

• Take ownership of large areas of our product and code base, with a focus on full-stack, product-focused engineering • Comfortable with both frontend and backend work • Deeply understand the breadth of our systems and lead us to effective end-to-end solutions and technical decisions • Help us build our team processes and culture

• Own full-stack product areas from concept through production, iteration, and scale. • Ship user-facing features quickly without sacrificing correctness or long-term maintainability. • Build across frontend and backend systems that power onboarding, dashboards, payments, and benefits management. • Translate real user and business needs into clear, pragmatic technical solutions. • Set and uphold a high bar for code quality, system design, and product polish. • Take responsibility for production systems, including reliability, debugging, and continuous improvement.

• Set the Strategy: Define the multi‑year technical strategy and roadmap • Manage the Portfolio: Develop the operating model for NIM Factory • Lead Leaders: Guide the NIM Factory engineering organization • Accelerate Day-0 Model Delivery: Manage the factory systems and platform capabilities • Establish the Operational Standard: Define and guide the full platform standards • Own Reliability, Security, and Compliance Outcomes: Partner with SRE and security leadership • Champion Open Source and Standards: Lead our upstream strategy and partnerships