• Combine strong technical skills with a “can-do” attitude • Advocate for automated testing, strong observability, and resilient design • Drive maintainable, well-tested code and modern development practices • Guide and mentor engineers across levels • Collaborate with engineering and product leaders

• Perform all or most of the primary duties listed in the job description • Specific tasks, responsibilities or competencies may be documented in the Team Member’s performance objectives

• Lead the development and implementation of strategy for product engineering • Maintain an established set of enterprise architecture artifacts • Drive advances in technologies to improve digital capabilities • Design and select business-critical storage and data center environments • Develop new applications to meet customer requirements • Guide teams in evaluating and implementing AI-enabled product features • Train or coach team members to improve performance

• 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.