Associate Director, Applied AI Engineering

Associate Director, Applied AI Engineering

The Enterprise AI organization at Humana is a pioneering force driving AI innovation across our Insurance and Center Well business segments. By partnering with world-class experts, we deliver cutting-edge AI capabilities that improve healthcare experiences and outcomes for millions of consumers.

We are seeking an Associate Director, Applied AI Engineering to lead and grow a high-performing team of AI engineers focused on building safe, scalable, and impactful AI solutions for the enterprise. This is a people-first leadership role for a technically strong engineering leader who is passionate about developing talent, establishing engineering excellence, and delivering AI-powered products at scale.

You will lead a multi-disciplinary engineering team responsible for production AI applications, agentic systems, conversational AI experiences, and intelligent automation capabilities while fostering a culture of innovation, accountability, inclusion, and continuous learning. Supporting Humana's enterprise AI book of work, this leader partners closely with data science, machine learning, product, business, architecture, security, and technology teams to ensure high-quality data is available for AI use cases across the organization.

The Associate Director applies cloud-native engineering practices, modern software development patterns, big data technologies, and AI/ML data enablement strategies to help Humana better serve its members.

This role requires a strong understanding of how organizational capabilities interrelate across departments and is responsible for identifying and resolving complex technical and operational challenges. The Associate Director may lead multiple managers or highly specialized professional associates and provides strategic and technical leadership for enterprise AI data engineering delivery.

• Team Leadership:
  Lead and grow a team of AI engineers building foundational services, frameworks, and tools for agentic AI applications—enabling consistent, scalable, and cost-effective development across the organization
• Industry Expertise:
  Stay current with industry trends in generative AI (e.g., foundation models, evaluation techniques, retrieval-augmented generation, fine-tuning approaches, and open-source tooling) and help the team apply them effectively
• Cross-Functional Collaboration:
  
  Drive cross-functional alignment with enterprise architecture, security, data engineering, Dev Ops, and application leads to ensure the generative AI platform is well-integrated and aligned with broader enterprise goals
• Mentorship:
  Mentor and coach AI engineers, helping them grow their technical skills and career paths while fostering a culture of experimentation, humility, and excellence
• Engineering Practices:
  Ensure strong engineering practices including CI/CD, automated testing, observability, and incident response for all services owned by the team
• Strategic Planning:
  Define and drive strategic plans, goals, and team performance based on company-wide agentic AI initiatives, balancing near-term needs with long-term platform investments
• System Design:
  Lead collaboration with application teams to understand their needs and design systems which solve complex challenges with reusable components on the agentic AI platform (e.g., LLM orchestration frameworks, experiment tracking, evaluation pipelines, model proxy/gateways, observability, etc.)
• Problem Solving:
  Work with broad guidelines and technical knowledge to solve highly complex problems with long-term impacts

• Master's degree or Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
• 7+ years of software engineering, AI engineering, or machine learning engineering experience.
• 2+ years of people leadership experience managing engineers or technical teams.
• Experience building and deploying AI/ML solutions in production environments.
• Strong proficiency in Python and modern software development practices.
• Experience with AI and machine learning frameworks such as PyTorch, Tensor Flow, Lang Chain, Lang Graph, or comparable technologies.

• Experience leading teams delivering Generative AI, RAG, conversational AI, or agent-based solutions.
• Experience working in healthcare, health insurance, or other highly regulated industries.
• Familiarity with AI observability, evaluation frameworks, governance, and safety practices.
• Strong communication and collaboration skills with the ability to explain technical concepts to diverse audiences.
• Experience partnering with product managers, data scientists, clinicians, compliance teams, and business stakeholders.
• Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Strong analytical and problem-solving skills, with the ability to think strategically and execute methodically.
• Demonstrated experience mentoring engineers and…