Health Admins is a leading third-party administrator in the healthcare space. Our Vision is to radically improve the way individuals interact with the healthcare system. We are committed to providing innovative and efficient health care solutions to our clients, ensuring they receive the best possible care and service. Our team is currently seeking a highly skilled and experienced VP of Engineering to join our dynamic team.

What We Are Looking For

Our ideal candidate will play a crucial role in managing our engineering environment, optimizing its performance, and driving continuous improvements to support our business goals and enhance our service delivery.

Every Team Member is Driven by a Commitment to Live out These Values:

1. Be Authentic: Be true and honest
2. Be Helpful: Pitch in and help
3. Be Innovative: Seek & embrace innovation
4. Be Accountable: Do what you say you are going to

Employees are expected to embrace our core values by being “A Hero in Action.” These values lay the foundation for the way we engage with each other and with our clients. They form the guardrails for our decision making and approach to problem solving.

Summary/Objective:

The VP of Engineering owns the technical vision, AI strategy, and engineering team for the organization's technology division. This is a hands-on leadership role — equal parts architect, builder, and team leader. The VP of Engineering makes the technical decisions that shape how we build, drives AI adoption across the organization, and is directly responsible for team culture, hiring, and how we scale. This role operates with startup-level autonomy inside an established business, requiring someone who stays close to the work while building the team and systems around them.

Essential Duties

1. Own the engineering team: manage daily scrums, lead weekly team meetings, and set direction on priorities, blockers, and technical approach
2. Define and drive the organization's AI and technology strategy, including platform selection, architecture patterns, and build-vs-buy decisions
3. Design and own AI/ML architecture across cloud platforms (AWS Bedrock, Google Vertex AI), establishing standards for RAG implementations, agent orchestration, and model selection
4. Contribute directly to production codebases; this is a hands-on role, not management from a distance
5. Architect agentic systems using modern patterns: MCP (Model Context Protocol), tool-use, function calling, and multi-step orchestration frameworks
6. Own the full data quality pipeline upstream of RAG: document ingestion architecture, parsing strategies, chunking methodology, and continuous iteration based on retrieval performance
7. Define and implement observability strategy, evaluation frameworks, production metrics, drift detection, and quality monitoring for deployed AI systems
8. Own cost optimization: model selection tradeoffs, token economics, usage monitoring, and budget forecasting at enterprise scale
9. Hire, mentor, and develop engineers; build a high-performing team culture that balances speed with code quality and system longevity
10. Establish and refine engineering processes: CI/CD pipelines, git workflow standards, SDLC documentation, code review practices, and onboarding programs
11. Develop AI-assisted development workflows and tooling that create a multiplying effect on team productivity
12. Define guardrails, compliance patterns, and scalability strategies for AI systems handling PHI
13. Collaborate with Operations, Compliance/Legal, and business stakeholders to identify, prioritize, and deliver AI use cases
14. Ensure all engineering and AI implementations comply with HIPAA and organizational data governance requirements
15. Report to the CTO on team performance, technical direction, and strategic roadmap

Skills Required

1. Proven ability to lead engineering teams while remaining technically hands-on
2. Strong architectural thinking with the ability to balance long-term vision against near-term delivery needs
3. Ability to translate complex technical concepts for non-technical stakeholders and align engineering efforts with business goals
4. Excellent verbal, written, and interpersonal communication skills
5. Experience building team culture, establishing engineering processes, and scaling development organizations
6. Ability to make sound technical decisions with incomplete information and operate autonomously with minimal oversight
7. Strong problem-solving skills and comfort working in ambiguous, fast-moving environments
8. Ability to identify and drive AI adoption opportunities across teams, creating repeatable frameworks and workflows
9. Solid time management skills with the ability to multitask and adjust priorities in a fast-paced environment
10. Must be proficient with Microsoft Office (intermediate Word, basic Excel)

Education/Experience

Required:

1. Bachelor's degree in Computer Science, Data Science, Engineering, Applied Mathematics, or related field; or equivalent practical experience
2. 7+ years in software engineering with progressive technical leadership
3. 3+ years in engineering management, including direct team leadership, hiring, and performance management
4. Demonstrated experience in architecting and deploying AI/ML systems in production environments
5. Track record of building or scaling engineering teams and establishing development processes
6. Experience designing systems that handle sensitive data with appropriate security and compliance controls

Preferred:

1. Master's degree in Computer Science, AI/ML, or related field
2. Experience in HIPAA-regulated environments
3. Insurance, healthcare payer, or healthshare industry experience
4. Experience operating in a startup or startup-like environment within a larger organization
5. History of driving AI adoption and building AI-augmented development workflows across teams

Technical Knowledge

Required:

1. Deep expertise in AWS Bedrock and/or Google Vertex AI
2. Proficiency with large language models (Claude, GPT, Gemini) and their APIs
3. Hands-on experience building RAG systems end-to-end — including document ingestion, parsing, chunking strategies, embedding models, vector databases, and retrieval optimization
4. Experience with vector databases (Pinecone, pgvector, or similar)
5. Strong background in prompt engineering, context engineering, and LLM integration patterns
6. Hands-on experience with agentic patterns: MCP (Model Context Protocol), tool-use/function calling, ReAct, Plan-and-Execute, or similar approaches
7. Experience with orchestration frameworks (LangGraph, LangChain, or similar)
8. Proficiency in Python and/or TypeScript for AI/ML development
9. Experience designing secure, scalable API ecosystems (REST, GraphQL)
10. Experience in architecting and maintaining CI/CD pipelines and development automation

Preferred:

1. Experience with LLM Ops tooling (LangSmith, Weights & Biases, Arize, Helicone, or similar)
2. Familiarity with HIPAA compliance frameworks and PHI data handling requirements
3. Experience with Salesforce development (Apex, LWC) is a plus
4. Knowledge of data governance and lineage tracking
5. Experience with AI observability and evaluation systems

What We Offer

1. Competitive salary and benefits package
2. Dynamic and innovative work environment
3. Opportunities for professional growth and development
4. Remote work flexibility

Equal Opportunity Statement

We are deeply committed to building a workplace and global community where inclusion is not only valued but prioritized. We are proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro diversity, disability, age or veteran status, or any other non-merit based or legally protected grounds. We are committed to providing reasonable accommodation to qualified individuals with disabilities in the employment application process.

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