Principal AI Engineer

The Principal AI Applied Engineer will define long-term AI technical strategy and architecture for enterprise healthcare AI-enabled products, while staying hands-on across prototyping, experimentation, and software delivery.

Role Overview

This position guides model strategy, platform direction, standards, governance, and cross-team adoption to support scalable, reliable, and responsible production AI systems. The role combines strategic architecture leadership with direct engineering involvement to advance both emerging capabilities and enterprise-grade operational readiness.

Key Responsibilities

• Define and drive 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.
• Lead organization-wide technical decision-making across model strategy, vendor selection, platform investments, build-versus-buy decisions, and shared infrastructure capabilities.
• Design and promote 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.
• Develop prototypes, proofs of concept, and reference implementations to reduce risk for emerging technologies and strategic platform investments.
• Conduct 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, communicating 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.
• Extensive experience designing cloud-native architectures and highly scalable, resilient systems.
• 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 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.

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.
• 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.

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

• Location: Louisville, KY 40201 (onsite)
• Work style: hybrid schedule requiring employees to work three days per week in the office and the remaining days remotely
• Salary: USD 206,600 - 284,300 per yearly
• Qualified candidates must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets.

Regulatory and Quality Focus

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 that meet high standards for privacy, reliability, and quality.