Vice President, Software Engineering

Primary Responsibilities

• Engineering & AI First Modernization Leadership
• Define and execute a multi-year AI-first modernization strategy aligned to the company’s priorities, growth goals, and operating model
• Lead the transformation of legacy platforms and applications toward AI-enabled, cloud-native, API-driven architectures that improve speed, resilience, and cost efficiency
• Manage multimillion-dollar portfolios and deliver measurable cost savings. Own engineering investment portfolios and budgets, with accountability for ROI, sequencing trade-offs, and value realization across modernization and AI initiatives
• Champion an AI-first engineering culture, where automation, intelligent workflows, code assist, and platform intelligence are embedded into how teams design, build, test, and operate software
• Build, lead, and scale a high-performing global engineering organization with a solid culture of accountability, continuous improvement, and inclusion, enabled by AI-driven productivity and insights
• Recruit, develop, and mentor senior engineering leaders capable of driving platform modernization and AI-led delivery at scale
• Platform & Application Modernization (AI Enabled by Design)
• Oversee the modernization of consumer and enterprise platforms supporting millions of users, ensuring scalability, security, maintainability, and intelligent observability
• Drive platform consolidation, rationalization, and reuse through shared services, common frameworks, reference architectures, and AI-powered platform capabilities
• Leverage AI to reduce technical debt, accelerate legacy remediation, improve testing and quality, and enhance developer experience
• Ensure product performance, reliability, and uptime meet or exceed expectations for mission-critical, public-facing systems, using AI-assisted monitoring, incident response, and resilience patterns
• Influence and help establish enterprise engineering, AI, and platform standards to ensure reuse, interoperability, and regulatory consistency across domains
• AI, Data & Intelligent Automation
• Establish AI as a foundational capability across the engineering ecosystem, from product features to internal platforms and operations
• Lead integration of GenAI, ML, and advanced analytics into products and platforms to enable personalization, automation, insight generation, and decision support
• Partner with Product, Data, and Analytics teams to ensure platforms enable AI-driven, data-informed user and operational experiences that deliver measurable value
• Ensure responsible AI adoption, including governance, data ethics, explainability, model risk management, and compliance with healthcare regulations
• Healthcare Compliance, Security & Responsible AI
• Ensure platforms and applications are built and operated in compliance with HIPAA, HITRUST, SOC 2, and other applicable standards
• Embed security, privacy, and responsible AI principles into architecture, tooling, and delivery practices ("secure and compliant by design")
• Proactively identify and mitigate risks related to data integrity, patient safety, AI model behavior, operational resilience, and information security
• Operational Excellence, AI Productivity & Cost Optimization
• Own execution across complex portfolios, including modernization roadmaps, budgets, sequencing, and capacity planning, with AI informing prioritization and trade-offs
• Drive cost optimization across cloud, tooling, and vendor ecosystems through architecture simplification, platform reuse, and AI-enabled efficiency
• Establish and track engineering health, modernization, and AI enablement KPIs, including developer productivity, time to value, platform reuse, and run cost reduction
• Advance best-in-class practices across Agile delivery, DevOps, SRE, and AIOps, embedding automation and intelligence throughout the SDLC and AI-SDLC
• Cross Functional & Executive Partnership
• Partner closely with Product, Clinical, Security, UX, and Executive leaders to ensure AI-first modernization delivers clear business, operational, and patient outcomes
• Serve as a strategic advisor and advocate for AI-driven engineering transformation in enterprise planning, investment decisions, and change initiatives

Required Qualifications

• 15+ years of software engineering experience, with 5+ years in senior engineering leadership roles
• Proven track record modernizing large-scale legacy platforms and establishing AI-enabled, cloud-native architectures
• Experience delivering and operating enterprise and consumer-grade systems at scale, supporting millions of users
• Demonstrated success leading matrixed, globally distributed engineering teams
• Deep expertise in cloud platforms (AWS, Azure, GCP), microservices, APIs, DevOps, application security, and modern SDLC and AI-SDLC practices
• Hands-on leadership integrating AI/ML and GenAI capabilities into production platforms and developer workflows
• Exceptional communication, influence, and executive stakeholder management skills

Preferred Qualifications

• Product-oriented engineering leader with a solid focus on platform reuse, developer experience, and AI-enabled productivity
• Experience leading AI-first transformation initiatives, including cloud migration, platform consolidation, and intelligent automation
• Proven experience deploying GenAI at scale across both customer-facing and internal engineering use cases
• Experience in healthcare, digital health, financial services, or similarly regulated industries
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field