VP, AI and Engineering
We are looking for a VP, AI and Engineering to join the leadership team at HDAI. You will report to the Chief Product Officer and lead the ML Operations, API Services, Frontend Engineering, and Cloud Engineering teams. These teams build and operate the HealthVision™ platform, which ingests clinical data from our health system partners, runs AI and ML inference, and delivers insights back to clinicians at the point of care.
Our platform runs on AWS, combines predictive ML models with LLM-powered clinical summarization, and serves results directly into EHR workflows. The challenge ahead is threefold: scale reliably as we onboard new health systems, deepen the AI product so clinicians get more value from every interaction, and do both while keeping cloud costs disciplined and maintaining the compliance posture (HIPAA, SOC 2, HITRUST) that our customers depend on. You will set the technical direction for how we tackle these problems and build the team and processes to execute against it.
A successful candidate has led engineering and applied AI teams in a regulated healthcare environment and knows what it takes to ship software that clinicians trust with patient care. You are as comfortable discussing model performance with a data scientist as you are reviewing an architecture decision with a cloud engineer or presenting a roadmap to a health system leader. At HDAI, we nurture a culture of continuous improvement, and one of the best assets of our leaders is a love for learning. We hope that you too share this goal. We are excited to have you as a part of this team!
Responsibilities
- Build, lead, and develop a high-performing engineering organization across multiple disciplines, setting clear goals, establishing operating rhythms, and creating meaningful career paths for the team.
- Own the technical vision and architecture of the HealthVision™ platform, making sound long-term bets while delivering on near-term commitments to customers and the business.
- Drive platform scalability and reliability as HDAI expands to new health system partners, ensuring that onboarding a new customer does not become a bespoke engineering project every time.
- Advance HDAI’s AI and LLM capabilities from their current production state into more powerful, cost-efficient, and clinically impactful tools—working closely with clinical and product leadership to identify the highest-value problems to solve next.
- Own cloud infrastructure strategy and cost management across HDAI’s AWS footprint, treating cost discipline as an engineering problem rather than an afterthought.
- Ensure that compliance (HIPAA, SOC 2, HITRUST) and data security are embedded in how the team designs and ships software, not bolted on after the fact.
- Partner with customer success leadership to support health system partnerships, including representing engineering in clinical and executive conversations with customers.
- Establish and evolve the engineering operating model: release management, quality assurance, incident response, on-call, and post-incident learning.
- Identify and implement leverage points—whether AI-assisted tooling, process improvements, or smart automation—that allow a lean team to punch above its weight.
- Contribute to company strategy as a member of the executive team, bringing a grounded technical perspective to business decisions.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field. An advanced degree (MS, PhD, or MBA) is a plus but not required.
- 10+ years of progressive engineering experience, with at least 4 years leading multi-team engineering organizations (managing managers, not just ICs).
- Meaningful experience with applied AI/ML in production systems. Familiarity with modern LLM application patterns (retrieval-augmented generation, structured extraction, prompt engineering at scale) is strongly preferred.
- Deep fluency with cloud-native architectures on AWS. You should be able to evaluate trade-offs in serverless vs. containerized designs, reason about event-driven systems, and have opinions about infrastructure-as-code.
- Experience shipping production software in a regulated healthcare environment—you understand what HIPAA compliance means in practice, not just in policy documents. Familiarity with SOC 2, HITRUST, HL7/FHIR, or EHR integration (especially Epic) is a significant plus.
- A track record of improving platform economics and performance—whether that’s reducing cloud spend, improving system throughput, or standardizing messy data pipelines—at meaningful scale.
- Experience supporting enterprise customer relationships from the engineering side, including technical onboarding, integration planning, and executive-level communication with health system leaders.
- Strong software engineering fundamentals. You may not write production code daily, but you have the judgment to set a high bar for quality and the credibility to hold the team to it.
- Excellent communication skills—written, verbal, and visual—with the ability to translate between clinical stakeholders, engineers, and business leaders.
- You exemplify strong accountability and ensure the quality of your work and your team.