Principal AI Engineer

Humana; Louisville (KY); Hybrid; USD 207,000 - 284,000; Full time

Benefits offered by this job

Medical, dental and vision benefits

401(k) retirement plan

Paid time off and holidays

Disability and life insurance

Job summary

Humana is seeking a Principal AI Applied Engineer to define long-term AI strategy and architecture for enterprise healthcare AI-enabled products, while prototyping and coding to de-risk new technologies. You will shape governance, platform investments, and cross-team adoption to deliver scalable, responsible AI systems.

Based in Louisville, KY with a hybrid schedule (three days in the office). You will mentor engineers, drive architecture reviews, and translate business priorities into technical

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 12+ years of software engineering experience, including large-scale distributed systems.
• Proven track record delivering production AI-enabled platforms/products at enterprise scale.
• Expert Python and/or TypeScript/JavaScript proficiency.

Responsibilities

• Define and lead long-term AI technical strategy, reference architecture, and technology roadmap for AI-enabled products and platforms.
• Set architectural patterns for retrieval systems, LLM orchestration, agentic workflows, and AI governance.
• Drive decisions on model strategy, platform investments, and shared infrastructure capabilities.
• Design scalable architectures balancing reliability, performance, security, compliance, maintainability, and cost.
• Establish engineering standards for evaluation, observability, and model lifecycle management.
• Mentor engineers through architecture reviews and technical sponsorship.

Skills

Python

TypeScript/JavaScript

Large-scale distributed systems

Education

Bachelor’s degree or equivalent practical experience

12+ years software engineering experience

Tools

Docker

Kubernetes

PostgreSQL

Gemini on Vertex AI

OCR/Document AI

Job description

Humana is hiring a Principal AI Applied Engineer to define long-term AI technical strategy and architecture for enterprise healthcare AI-enabled products, while also contributing hands-on through prototyping, experimentation, and software development. This role shapes model strategy, platform investments, standards, governance, and cross-team adoption to deliver scalable, reliable, responsible production AI systems.

Key Responsibilities

• Define and lead the long-term technical strategy, reference architecture, and technology roadmap for AI-enabled products and platforms.
• Set architectural patterns and best practices for retrieval systems, LLM orchestration, agentic workflows, human-in-the-loop processes, evaluation frameworks, and AI governance.
• Drive organization-wide technical decisions on model strategy, vendor selection, platform investments, build-versus-buy choices, and shared infrastructure capabilities.
• Design scalable architectures that balance reliability, performance, security, compliance, maintainability, and cost efficiency.
• Establish engineering standards for evaluation, observability, model lifecycle management, responsible AI practices, and operational excellence.
• Build prototypes, proofs of concept, and reference implementations to reduce risk in emerging technologies and strategic platform investments.
• Lead cross-functional architecture reviews and provide technical guidance across multiple engineering teams.
• Mentor Lead Engineers, Senior Engineers, and emerging technical leaders through architecture reviews, design feedback, coaching, and technical sponsorship.
• Develop and communicate technical roadmaps aligned to business strategy and organizational objectives.
• Partner with executive leadership to translate business priorities into technical strategies, and communicate technical opportunities, risks, and tradeoffs.
• Represent engineering in strategic vendor evaluations, compliance discussions, governance reviews, and enterprise planning initiatives.
• Drive adoption of common platforms, standards, and engineering practices across teams.
• Ensure AI systems are designed and operated to meet privacy, security, compliance, governance, and auditability requirements.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 12+ years of software engineering experience, including extensive experience designing and operating large-scale distributed systems.
• Proven experience designing, delivering, and operating production AI-enabled platforms or products at enterprise scale.
• Deep expertise in large language model technologies, AI platform design, retrieval-augmented generation (RAG), agentic systems, orchestration frameworks, evaluation methodologies, and AI operations.
• Experience designing cloud-native architectures and highly scalable, resilient systems.
• Demonstrated ability to define technical direction that influenced teams, organizations, or product portfolios beyond direct reporting relationships.
• Experience establishing engineering standards, architectural frameworks, or technical platforms adopted across multiple teams.
• Strong understanding of AI operational challenges, including model reliability, latency, cost optimization, governance, observability, and risk management.
• Demonstrated success influencing executive stakeholders and driving organizational decisions through technical leadership and evidence-based recommendations.
• Expert-level proficiency in Python and/or TypeScript/JavaScript.
• Ability to prototype, debug, review, and contribute code across multiple layers of the technology stack.

Preferred Qualifications

• Experience leading AI platform strategy across multiple business units or product organizations.
• Experience developing enterprise standards for AI evaluation, testing, observability, governance, and responsible AI practices.
• Expertise evaluating and managing AI vendor ecosystems across multiple model providers and platform technologies.
• Experience building shared AI infrastructure and platform capabilities consumed by multiple engineering teams.
• Experience with agentic architectures, Model Context Protocol (MCP), workflow orchestration, autonomous systems, and emerging AI frameworks.
• Experience operating AI systems at significant scale while managing performance, reliability, and cost tradeoffs.
• Experience in regulated industries such as healthcare, financial services, life sciences, or government.
• Deep understanding of privacy, security, compliance, governance, and risk management requirements in highly regulated environments.
• Experience driving adoption of AI-assisted software development practices across engineering organizations.
• Experience advising executive leadership on emerging technologies, platform strategy, and enterprise architecture decisions.
• Exceptional communication, leadership, collaboration, and strategic problem-solving skills.

Technologies

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

Leadership Expectations

• Serve as the highest-level technical authority within the AI Applied Engineering organization.
• Influence organizational outcomes through technical excellence, credibility, and demonstrated results rather than formal authority alone.
• Balance innovation with operational discipline and long-term sustainability.
• Establish scalable technical standards that enable teams to move faster while maintaining quality and reliability.
• Drive alignment across engineering, product, business, clinical, compliance, and executive stakeholders.
• Build organizational capability by mentoring and developing the next generation of technical leaders.
• Foster a culture of engineering rigor, continuous learning, accountability, and responsible AI development.

Success Profile

• Respected technical leadership combining strategic thinking with hands-on execution.
• Organizational influence built on technical expertise, data-driven decision-making, and working solutions rather than formal authority.
• Motivation for difficult, long-horizon problems and comfort making high-impact decisions affecting multiple teams and products.
• View AI architecture, governance, reliability, and responsible deployment as core engineering disciplines.
• Continue building through architecture, experimentation, and code, grounded in real experience developing, testing, and operating production systems.

Location and Work Style

Louisville, KY 40201 (Onsite). Hybrid schedule requires 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.

Compensation

USD 206,600 - 284,300 per year.

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

Additional Information

This role operates in a highly regulated environment where responsible handling of sensitive and protected information is fundamental. Success requires a commitment to building secure, compliant, auditable, and trustworthy AI systems meeting high standards for privacy, reliability, and quality.