VP of Engineering

Health Admins

VP of Engineering leading engineering team and AI strategy for healthcare technology solutions. Ensuring high-quality software and AI implementations to support business goals.

Posted 4/28/2026full-timeRemote • Texas • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AWSCloudSDLC

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

Competitive salary and benefits package
Dynamic and innovative work environment
Opportunities for professional growth and development
Remote work flexibility

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI architectureML architecturecloud platformsAWS BedrockGoogle Vertex AICI/CD pipelinesdata quality pipelineobservability strategyproduction metricssoftware engineering

Soft Skills

team leadershipmentoringcollaborationcommunicationperformance managementproblem-solvingstrategic thinkingorganizational skillsculture buildingprocess refinement

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Data ScienceBachelor's degree in EngineeringBachelor's degree in Applied Mathematics