Principal AI Engineer

About the role

We build a platform that transforms millions of clinical documents into trusted, actionable data using large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations, and route difficult cases to human experts. As a Principal AI Applied Engineer you will define the technical strategy, architectural standards, and long‑term vision for AI‑enabled products across the organization while remaining deeply hands‑on in prototyping, experimentation, architecture, and software development. This is the highest‑level individual contributor role within the AI Applied Engineering organization.

Key Responsibilities

• Define and drive the long‑term technical strategy, reference architecture, and technology roadmap for AI‑enabled products and platforms.
• Establish architectural patterns and best practices for retrieval systems, LLM orchestration, agentic workflows, human‑in‑the‑loop processes, evaluation frameworks, and AI governance.
• Lead organization‑wide technical decision‑making regarding model strategy, vendor selection, platform investments, build‑versus‑buy decisions, and shared infrastructure capabilities.
• Design scalable architectures that balance reliability, performance, security, compliance, maintainability, and cost efficiency.
• Set engineering standards for evaluation, observability, model lifecycle management, responsible AI practices, and operational excellence.
• Build prototypes, proofs of concept, and reference implementations that de‑risk 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 with business strategy and organizational objectives.
• Partner with executive leadership to translate business priorities into technical strategies and communicate technical opportunities, risks, and trade‑offs.
• 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 in accordance with 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 track record of 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.
• Extensive experience designing cloud‑native architectures and highly scalable, resilient systems.
• Demonstrated ability to define technical direction that influences 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.
• Successful experience 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 trade‑offs.
• Experience working 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.

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.
• 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 in This Role

Successful candidates are respected technical leaders who combine strategic thinking with hands‑on execution. They influence organizations through technical expertise, data‑driven decision‑making, and working solutions rather than formal authority alone. They are energized by difficult, long‑horizon problems and are comfortable making high‑impact decisions that affect multiple teams and products. They view AI architecture, governance, reliability, and responsible deployment as core engineering disciplines and remain active builders, grounding strategy in real experience developing, testing, and operating production systems.

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

Work Style & Schedule

This position follows a hybrid work schedule, requiring three days per week in the office and the remaining days remote. Candidates must reside within, or be willing to relocate to, a commutable distance from one of the talent markets.

Pay

The estimated base pay range for full‑time (40 hours per week) employment is $206,600 – $284,300 per year, subject to geographic location and individual qualifications. This role is eligible for a performance‑based bonus incentive plan.

Benefits

Humana offers a competitive benefits package that supports whole‑person well‑being, including medical, dental, and vision coverage; a 401(k) retirement savings plan; paid time off (including holidays, parental and caregiver leave); short‑term and long‑term disability; life insurance; and additional wellness and financial programs.