Humana is hiring a Lead AI Applied Engineer to provide hands-on technical leadership for production AI systems built around LLMs in a highly regulated healthcare environment. You will own architecture and engineering standards, while designing and building the most critical components needed to deliver reliable, scalable, and auditable AI solutions that support healthcare decisions at meaningful scale.
This is a hybrid role based in Louisville, KY, with 40 scheduled weekly hours, and it requires a strong focus on operational excellence, privacy, security, governance, and auditability.
Responsibilities
- Lead the architecture of production AI systems where LLMs are foundational to the product experience.
- Make key technical decisions covering model selection, system boundaries, platform architecture, and build-versus-buy strategies.
- Own the highest-risk, highest-impact technical challenges involving reliability, explainability, and correctness.
- Establish standards that influence engineering culture and how the team builds and ships AI products.
- Work on systems operating at significant scale, processing millions of documents and supporting healthcare decisions across a large member population.
- Partner with skilled engineers while staying deeply hands-on in coding, design, and production operations.
- Simplify complex solutions and drive pragmatic engineering decisions that maximize business value.
- Own architecture, design, and evolution of full-stack AI applications, including LLM pipelines, retrieval systems, agentic workflows, human-in-the-loop processes, and supporting platform services.
- Design and implement scalable AI solutions emphasizing reliability, accuracy, auditability, performance, and cost efficiency.
- Build and maintain the most complex and high-risk system components where architecture and implementation decisions have business impact.
- Define and enforce engineering standards for AI systems, including evaluation methodologies, structured outputs, observability, testing, fallback strategies, latency optimization, and cost controls.
- Lead technical design reviews and guide architecture decisions related to 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 goals into clear technical strategies, roadmaps, and executable workstreams.
- Provide technical leadership across multiple projects to ensure 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 meet business and regulatory requirements.
- Own operational excellence, including deployment strategies, monitoring, incident management, and production reliability.
- Ensure solutions comply with privacy, security, governance, and audit requirements in a regulated healthcare environment.
- Foster a culture of ownership, continuous learning, mentorship, and accountability, and drive alignment across teams.
Requirements
- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
- 8+ years of software engineering experience, including designing and operating production systems at scale.
- Proven track record of 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 architectural decisions for systems where AI is a core product experience component.
- 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 are part of 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: This role operates in a highly regulated environment where handling sensitive and protected data is a fundamental requirement and a core part of engineering culture. Success depends on building secure, compliant, auditable, and trustworthy AI systems. The work style is hybrid, requiring employees to work three days per week in the office and the remaining days remotely. Qualified candidates must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets.
Location: Louisville, KY (hybrid)
Pay range: USD 170,800 - 234,800 per year
Schedule: 40 hours per week
