Lead Software Engineer

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The Lead Software Engineer codes software applications based on business requirements. The Lead Software Engineer works on problems of diverse scope and complexity ranging from moderate to substantial.

The Lead Software Engineer standardizes the quality assurance procedure for software. Oversee testing and debugging and develops fixes. Research complaints and make necessary adjustments and/or recommendations to resolve complex software related issues. Advise executives to develop functional strategies (often segment specific) on matters of significance. Exercise independent judgment and decision making on complex issues regarding job responsibilities and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action.

Use your skills to make an impact

Key Responsibilities
- MVP and Product Ownership: Own AI products from initial concept through MVP, pilot, and production readiness. Define the product and technical approach, make pragmatic scope decisions, and take direct responsibility for delivering solutions that create measurable value for clinicians, members, and internal teams.
- Rapid Prototyping and Iteration: Build and launch proofs of concept and working MVPs quickly. Use feedback, experimentation, and real-world usage data to validate assumptions, refine requirements, and continuously improve product capabilities.
- Clinical and Product Partnership: Collaborate closely with product managers, designers, clinicians, and data stakeholders to understand care delivery workflows and translate them into well-scoped, AI features.

- Technical Decision-Making and Delivery: Make and clearly communicate foundational architecture and technology decisions while balancing speed, scalability, maintainability, and operational risk. Establish lightweight engineering practices that enable rapid delivery without compromising quality.
- HIPAA Compliance and Responsible AI: Ensure all AI systems are designed, deployed, and monitored in compliance with HIPAA and Humana's Responsible AI standards, including participation in AIRB and Responsible AI Council review processes where applicable.

Required Qualifications

- B.S. or M.S. in Computer Science, Engineering, or a related field (or equivalent experience)
- 8+ years of software engineering experience
- Deep, hands-on experience building with large language models and orchestration frameworks (LangChain, LlamaIndex, or equivalent)
- Strong proficiency in Python, Typescript and modern ML tooling (Hugging Face, PyTorch, or similar)
- Proven experience designing and deploying RAG pipelines and vector search systems in production
- Working knowledge of model fine-tuning approaches (LoRA, RLHF, instruction tuning, or equivalent)
- Experience designing and building multi-agent AI systems, including agent orchestration, tool use, and sandboxed execution environments
- Demonstrated ownership of complex AI systems end-to-end, from architecture through production operation
- Understanding of HIPAA requirements and secure handling of protected health information (PHI)
- Strong written and verbal communication skills across technical and non-technical audiences
- Hands-on experience with AI-assisted development tools and LLM coding harnesses (Claude Code, Pi Agent, Cursor, Codex, or similar)
- Experience collaborating with Product Management to shape product direction, gather requirements, and lead the design and development of scalable, customer-focused applications. - Experience rapidly building prototypes using agent coding harnesses (claude code, codex, etc)

Preferred Qualifications
- Experience in healthcare, clinical informatics, or other highly regulated industries
- Experience designing and implementing custom LLM and agent evaluation frameworks, including automated eval pipelines, benchmark construction, and output quality assessment at scale