Director, Software Engineering

Essential Job Duties

• Own engineering delivery, maintenance, and production operations responsibilities for assigned areas across the HHAeXchange SaaS platforms.
• Deliver new features and optimize existing components with focus on code quality, scalability, performance, security, stability, and maintainability.
• Ensure effective incident response, troubleshooting, and operational execution for production systems.
• Establish clear accountability and execution standards across engineering teams.
• Provide leadership across multiple engineering teams, including engineering managers, tech leads, and individual contributors.
• Drive predictable delivery through strong planning, prioritization, and execution discipline.
• Set expectations for performance and accountability across teams.
• Coach leaders and engineers through mentorship, feedback, and professional development.
• Drive modernization and platform evolution, including cloud and architectural improvements.
• Advance cloud-native principles and best practices in new development and enhancements.
• Partner with architecture leadership to ensure system designs meet enterprise standards.
• Promote continuous improvement through refactoring, technical debt reduction, and platform upgrades.
• Lead engineering governance and operational readiness, ensuring consistency and quality across releases.
• Participate in or support architecture review and design review processes.
• Ensure proper release planning, change management, and production readiness practices.
• Establish effective standards for deployment quality, rollback readiness, and operational support coverage.
• Drive development and adoption of AI-enabled capabilities across the HHAeXchange SaaS platforms.
• Partner with Product, Architecture, and Data/AI stakeholders to identify and deliver high-impact AI use cases that improve operational efficiency, compliance, and customer outcomes.
• Ensure AI features are built with strong standards for quality, performance, security, privacy, and reliability.
• Lead adoption of AI-assisted SDLC tools and practices to improve engineering velocity and effectiveness (e.g., Cursor and other modern AI coding tools).
• Establish best practices, guardrails, and repeatable workflows for AI-supported development, testing, code review, and documentation.
• Measure and improve productivity and quality outcomes through responsible use of AI tooling while maintaining engineering standards and maintainability.
• Work closely with VP, Software Engineering and CTO to formulate strategies and execute the vision.
• Collaborate with Product Managers on future product strategy.
• Collaborate and work with the team with a positive and open-minded attitude.
• Share domain and technical expertise, providing technical mentorship and cross-training to other peers and team members.
• Enable automation of configuration management of development, quality assurance, and production environments as well as automation of continuous integration and continuous delivery.
• Supervise training and development of software engineering staff.
• Support recruiting engineering personnel, technical staffing, and project teams’ formation.

Other Job Duties

• Other duties as assigned by supervisor or HHA exchange leader.

Travel Requirements

• Travel up to 10%, including overnight travel

Required Education, Experience, Certifications and Skills

• 10+ years of experience in developing, deploying, monitoring, and supporting applications.
• Minimal 5+ years of experience in a leadership position managing highly skilled software development teams across US and around the globe.
• Proven experience leading development of AI-enabled software products, including applying machine learning, automation, or intelligent decisioning to enterprise SaaS platforms.
• Experience driving adoption of AI-assisted software development lifecycle (SDLC) tools to improve engineering productivity, quality, and delivery speed (e.g., AI-powered coding, testing, and documentation tools such as Cursor or similar platforms).
• Strong understanding of responsible AI practices, including quality, security, privacy, explainability, and maintainability considerations in production systems.
• Strong requirements gathering, analysis, and questioning skills.
• Strong understanding of software engineering best practices including design, development, testing, release, and operational support.
• Experience leading teams that support business-critical enterprise SaaS systems (e.g., healthcare platforms, billing, ERP, workflow systems).
• Ability to review and guide engineering execution across designs, code quality, production deployments, performance, and stability improvements.
• Familiarity with modern architecture and operational practices including API and service-based architecture, cloud infrastructure, and incident response.
• Extensive experience with .NET, Angular, Web Services/APIs, and SQL Server (or comparable enterprise SaaS technology stacks).
• Experience with containerization and orchestration technologies such as Docker and Kubernetes (or equivalent platforms).
• Experience with AWS cloud services. AWS certification is a plus.
• Excellent communication skills and ability to drive outcomes across engineering and cross-functional partners.
• Proven ability to lead through ambiguity, manage competing priorities, and deliver predictable results.
• Willingness to explore and adopt AI tools responsibly to enhance productivity and innovation in your role