Vice President of Software Engineering
Summary
A hands-on VP of Software & Data Engineering owning engineering, data, QA and DevOps teams at a growth-stage healthcare fintech. The role modernizes patient engagement, payments and provider platforms toward cloud-native, API-first architecture, deploys ML/GenAI to production, and maintains HIPAA/PCI compliance, using .NET, SQL, Azure/AWS and modern data stacks.
Our client, an award-winning, growth-stage healthcare fintech company, is hiring a VP of Software & Data Engineering to lead the technology behind its patient platform. This hands-on leader will own engineering and data strategy, scale the team, lead enterprise AI deployment and modernize a highly regulated platform that serves health systems and patients nationwide.
What You'll Do
- Set the software and data roadmap and lead engineering, data, QA and DevOps teams
- Modernize the patient engagement, payments and provider platforms toward a cloud-native, API-first architecture
- Own integrations with health system EHR and revenue cycle systems, lending partners and payment processors
- Build a modern data platform that powers risk, collections and client reporting
- Lead AI strategy and deployment, taking ML and generative AI from pilot to production in areas such as payment propensity, patient engagement, servicing automation and engineering productivity
- Set responsible AI governance, including model monitoring, explainability, bias testing and HIPAA-safe data use
- Drive engineering excellence through CI/CD, automated testing, observability and clear delivery metrics
- Maintain security and compliance (HIPAA, HITRUST, PCI DSS, SOC 2) and platform reliability
- Manage the engineering budget, vendors and build-vs-buy decisions
What You Bring
- 10+ years in software and/or data engineering
- Deep experience with .net and SQL.
- Experience scaling platforms in healthcare, payments, lending or revenue cycle management
- Deep knowledge of cloud (Azure or AWS), microservices, APIs and modern data stacks (e.g., Snowflake, Databricks, Fabric, dbt)
- Track record in regulated environments (HIPAA, HITRUST, PCI DSS or SOC 2)\
- Hands-on experience deploying ML or generative AI solutions into production, including MLOps and LLM platforms (e.g., Azure OpenAI, AWS Bedrock)
- Proven ability to hire, develop and retain strong engineering teams
- Bachelor's degree in Computer Science, Engineering or a related field