Vice President, AI Engineering
Leads AI engineering at Komodo Health, owning platform architecture, LLM integration, compliance, and scaling the Marmot generative AI platform for healthcare insights. Requires 10+ years leading AI teams in high-trust environments with hands-on LLM expertise.
The Opportunity
As VP of AI Engineering, you will own the technical foundation for AI across Komodo Health—designing the agent runtimes, orchestration layers, evaluation systems, and reference architectures that every product and engineering team builds on. You’ll lead a team of engineers and data scientists scaling Marmot, our generative AI platform that transforms complex healthcare data into enterprise-grade insights, while establishing the standards, observability, and governance required to deliver AI in a regulated healthcare environment.
Looking back on your first 12 months at Komodo Health, you will have accomplished...
- Established AI Engineering Standards: Defined reference architectures, shared evaluation frameworks, and governance models that give teams a reliable, auditable foundation to build on.
- Hardened the AI Platform for Scale and Trust: Built evaluation, regression testing, observability, and lifecycle governance layers into Marmot.
- Made AI-Native Development the Default: Teams across engineering actively use AI development tools (Claude Code, Copilot, etc.) for design, prototyping, refactoring, and system reasoning.
- Secured Strategic Alignment: Partnered effectively with the C-Suite, Product, and Sales leadership to ensure AI infrastructure directly supports Komodo’s most critical commercial outcomes.
Responsibilities
- AI Platform Architecture: Design and ship agent runtimes, orchestration layers, and shared evaluation systems. Define reference architectures and engineering standards across the AI org.
- LLM Systems Engineering: Own the integration of Large Language Models and NLP systems into production, engineering deterministic control planes around probabilistic models.
- Trust and Compliance Engineering: Build auditability, regression testing, and lifecycle governance into every AI system.
- Build vs. Buy Decisions: Evaluate, select, and integrate AI tooling and vendor solutions.
- Cross-Functional Force Multiplication: Partner with Engineering, Data Science, Product, and IT to embed AI capabilities into core workflows.
- Technical Advisory to Leadership: Serve as the primary technical advisor for senior stakeholders.
Requirements
- 10+ years of experience leading technical organizations within B2B SaaS or high-scale data environments.
- Proven track record designing and shipping foundational AI infrastructure including agent runtimes, orchestration layers, evaluation frameworks, and observability.
- Deep experience delivering AI systems in regulated, high-trust environments with auditability, regression testing, and lifecycle governance.
- Demonstrated use of AI tools as force multipliers in your own engineering workflow.
- Proven leadership building high-performing AI/ML teams.
Nice to Have
- Healthcare, life sciences, or health data domain experience.
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