Lead AI Engineer

Lead AI Applied Engineer role at Humana providing technical leadership for production AI systems using LLMs in a regulated healthcare environment.

Responsibilities

• Lead architecture for production AI systems where LLMs are foundational to the product experience
• Own key technical decisions across model selection, system boundaries, platform architecture, and build-versus-buy strategy
• Own highest-risk and highest-impact challenges in reliability, explainability, and correctness
• Set engineering standards that influence team practices for building and shipping AI products
• Work on systems operating at scale, processing millions of documents and supporting healthcare decisions for a large member population
• Stay hands-on across coding, design, and production operations while partnering with skilled engineers
• Simplify complex technical solutions and drive pragmatic decisions that maximize business value
• Own end-to-end architecture and evolution of full-stack AI applications including:
  • LLM pipelines
  • Retrieval systems
  • Agentic workflows
  • Human-in-the-loop processes
  • Supporting platform services
• Design and implement scalable AI solutions prioritizing reliability, accuracy, auditability, performance, and cost efficiency
• Build and maintain the most complex, high-risk system components where architecture and implementation drive major business impact
• Define and enforce engineering standards for AI systems, including:
  • Evaluation methodologies
  • Structured outputs
  • Observability
  • Testing
  • Fallback strategies
  • Latency optimization
  • Cost controls
• Lead technical design reviews and guide architecture decisions for platform capabilities, AI systems, integrations, infrastructure, and software patterns
• Evaluate and recommend technologies, frameworks, AI models, and third-party solutions based on technical and business requirements
• Translate ambiguous business objectives into technical strategies, roadmaps, and executable workstreams
• Provide technical leadership across multiple projects, ensuring alignment with architectural standards and long-term platform objectives
• Mentor and coach engineers through design reviews, code reviews, pair programming, and technical guidance
• Partner with product, engineering, clinical, and operational stakeholders to deliver solutions aligned to business and regulatory needs
• Own operational excellence, including deployment strategies, monitoring, incident management, and production reliability
• Ensure privacy, security, governance, and audit compliance within a regulated healthcare environment
• Drive alignment across teams and stakeholders for delivery of strategic initiatives

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• 8+ years of software engineering experience, including designing and operating production systems at scale
• Proven track record delivering AI-enabled products or platforms into production environments
• Deep hands-on experience integrating and operating LLMs in business-critical workflows
• Experience designing systems using structured outputs, tool calling, retrieval-augmented generation (RAG), agentic workflows, orchestration frameworks, and evaluation pipelines
• Experience making architecture decisions for systems where AI is a core component of the product experience
• Demonstrated success leading technical initiatives across engineering teams, including architecture reviews, technical planning, mentoring, and delivery execution
• Strong programming skills in Python and/or TypeScript/JavaScript
• Experience designing and operating distributed systems, APIs, data platforms, and cloud-native applications
• Strong understanding of reliability engineering, system performance, scalability, and operational excellence
• Ability to balance tradeoffs across quality, latency, cost, security, and maintainability

Technology stack

• TypeScript
• React / Next.js
• Python
• PostgreSQL
• Gemini on Vertex AI
• OCR and Document AI technologies
• Docker
• Kubernetes
• Modern CI/CD platforms and tooling

Benefits

• Medical, dental and vision benefits
• 401(k) retirement savings plan
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
• Short-term and long-term disability
• Life insurance
• Bonus incentive plan (eligible)

Preferred qualifications

• Experience taking AI products from concept through production deployment and long-term operational ownership
• Experience developing AI systems where LLMs support critical decision-support or operational workflows
• Expertise in evaluation frameworks, benchmark datasets, regression testing, model quality measurement, and human review processes
• Experience with agentic systems, Model Context Protocol (MCP), workflow orchestration, multi-step reasoning frameworks, and AI observability platforms
• Experience with React, Next.js, modern frontend technologies, and full-stack application development
• Experience deploying and managing workloads using Kubernetes, Docker, modern CI/CD platforms, and cloud-native technologies
• Experience with Google Cloud Platform, Azure, AWS, Vertex AI, or comparable AI and cloud infrastructure platforms
• Experience working in highly regulated industries such as healthcare, financial services, or government
• Knowledge of privacy, compliance, security, and governance frameworks impacting AI and data-driven applications
• Experience implementing AI-assisted development practices that improve engineering productivity and delivery speed
• Excellent communication, collaboration, problem-solving, and leadership skills

Additional information

• Location: Louisville, KY (hybrid)
• Schedule: hybrid work schedule, requiring employees to work three days per week in the office and the remaining days remotely
• Operating environment: highly regulated
• Sensitive and protected data handling is a core part of the engineering culture
• Work requires building secure, compliant, auditable, and trustworthy AI systems
• Qualified candidates must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets
• Scheduled weekly hours: 40

Compensation: USD 170,800 - 234,800 per year