Job Description

Navina is a fast-growing digital health SaaS company that’s on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use Navina’s AI-powered solution that transforms complex and fragmented patient data into concise “patient portraits" and actionable clinical insights at the point of care. With Navina, physicians experience less burnout, reduce missed diagnoses, and can devote more time giving better care to their patients.

Navina has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations, including Privia Health and Agilon.

Navina’s system aggregates medical data from all available data sources into a single clinical snapshot, highlighting critical information and delivering it to the clinician at the point of care. This is done using cutting-edge Deep Learning and NLP algorithms.

Navina’s AI organization has grown into multiple strong teams (Data Science, Medical Research, Analytics/BI) working closely with an MLE squad. While team leads own delivery and execution, the organization is missing a senior, hands-on technical leader whose role is to:

• Provide system-level AI architectural guidance
• Drive hands-on applied innovation
• Establish AI best practices and compliance readiness
• Serve as a senior technical sounding board across teams

This role fills that gap.

It is a director-level individual contributor role, designed to bring deep technical leadership, fast execution, and architectural clarity

Responsibilities

1. AI Architecture & Technical Leadership

• Guide AI architectural direction across Navina’s platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
• Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
• Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
• Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.

This role influences judgment, clarity, and experience, not through blocking authority.

2. Hands-on Applied Innovation (Core Pillar | ~50%)

• Spend at least 50% of time hands-on, building:
• End-to-end AI prototypes
• Technical demos and proofs of concept
• Exploratory implementations of new AI capabilities

Drive applied innovation that:

• De-risks new technologies
• Demonstrates feasibility and impact
• Informs product direction and business opportunities
• Build fast, concrete examples that teams can learn from and extend.
• Transition successful prototypes to team ownership for further development and scaling.

This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering

3. Best Practices & Technical Enablement

• Define and promote best practices for applied AI development, including:
• Rapid prototyping and “vibe coding.”
• Agent design, orchestration, and evaluation patterns
• Experimentation, benchmarking, and validation workflows
• Help teams align on shared technical patterns, tools, and standards.
• Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
• Lead technical deep dives, architecture discussions, and design reviews.

4. AI Compliance & Regulatory Enablement (Technical Scope)

• Ensure Navina’s AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
• Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
• Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
• Serve as a technical point of reference for AI compliance questions.

Regulatory ownership and formal approvals remain with Legal and other relevant functions.

Requirements

• Proven experience designing and building complex AI systems that have been successfully delivered to production, with an end-to-end understanding of research, architecture, validation, and production handoff.
• Strong hands-on experience with modern AI approaches, including Machine Learning, Deep Learning, and LLM-based systems; experience with agentic AI systems or orchestration patterns is a strong advantage.
• Demonstrated ability to move quickly from idea to working prototype, with a strong passion for hands-on experimentation and applied innovation.
• Experience working in environments involving sensitive data and regulatory constraints, with an understanding of how these considerations shape AI system design.
• Excellent system-level technical judgment, including the ability to identify risks, tradeoffs, and unintended consequences in AI systems.
• Proven ability to act as a technical leader without formal authority, influencing and guiding senior peers through collaboration and expertise.
• Strong communication and interpersonal skills, with the ability to explain complex technical concepts to diverse stakeholders.
• Ability to contribute to clear technical and AI-related compliance documentation.
• High proficiency in Python and modern AI/ML tooling.

Optional / Nice-to-Have

• Deep experience in NLP, NLU, or clinical text processing.
• Experience deploying LLMs or agent-based systems in production.
• Familiarity with cloud-native ML stacks (AWS, Docker, Kubernetes).