Senior Director of Engineering & Data

Our client, a growth-stage healthcare fintech company, is hiring a Senior Director of Engineering & Data to lead the teams behind its patient platform. Reporting to the CTO, this hands-on leader will own software and data engineering execution, scale the team, drive enterprise AI deployment and modernize a highly regulated platform that serves health systems and patients nationwide. This role is for someone who takes ownership, drives projects to completion and isn’t afraid to push back.

Make sure to read the full description below, and please apply immediately if you are confident you meet all the requirements.
What You'll DoLead software engineering, data engineering, QA and DevOps teams, partnering with the CTO on the technology roadmap and owning its executionModernize the patient engagement, payments and provider platforms toward a cloud-native, API-first architectureOwn integrations with health system EHR and revenue cycle systems, lending partners and payment processorsBuild a modern data platform that powers risk, collections and client reportingTake ML and generative AI from pilot to production in areas such as payment propensity, patient engagement, servicing automation and engineering productivityImplement responsible AI practices, including model monitoring, explainability, bias testing and HIPAA-safe data useEstablish engineering processes and delivery standards through CI/CD, automated testing, observability and clear metricsPartner with product leadership to shape priorities, push back on scope and timelines when needed, and keep delivery realisticMaintain security and compliance (HIPAA, HITRUST, PCI DSS, SOC 2) and platform reliabilityManage team budget, vendors and build-vs-buy recommendations
What You Bring10+ years in software xzbcwsv and/or data engineeringDeep experience with .net and SQL.Deep knowledge of cloud (Azure or AWS), microservices, APIs and modern data stacks specifically SnowflakeTrack 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 teamsBachelor's degree in Computer Science, Engineering or a related field