Sr. Manager- Software Engineering- Healthcare IT

Merative is a company that provides medical imaging solutions to healthcare organizations. They are seeking a proven and forward-thinking Sr. Manager, Software Engineering to lead a team of 10–15 software engineers delivering enterprise SaaS solutions, focusing on technical excellence and AI-assisted development practices.

Responsibilities:

• Set and evolve the technical direction for the team, ensuring architectural decisions align with product goals, scalability requirements, and industry best practices
• Champion the adoption of GenAI-powered developer tooling (e.g., GitHub Copilot, Claude Code) to accelerate delivery and improve code quality
• Conduct and guide rigorous code reviews, architecture discussions, and design sessions to maintain high engineering standards
• Stay current with emerging technologies, frameworks, and AI/ML advancements relevant to enterprise SaaS development
• Has full accountability for technical output within the group, ensuring solutions are scalable, secure, and maintainable
• Lead, mentor, and grow a team of 10-15 engineers of varying experience levels, including senior engineers and individual contributors
• Own the full talent lifecycle: hiring, onboarding, performance management, career development, compensation planning, and retention
• Foster a culture of technical curiosity and continuous improvement, where engineers feel empowered to experiment with new technologies and tools, including AI-assisted workflows
• Identify skills gaps and build targeted development plans, advocate for team members’ growth and promotion opportunities
• Responsible for a major engineering function, demonstrating strong leadership and management skills with the ability to manage mid-sized teams
• The role’s core accountability is ensuring the team delivers high-quality, reliable software that meets enterprise-grade reliability and compliance requirements
• Partner with Product Management and Design to translate business requirements into well-scoped engineering deliverables
• Own sprint planning, capacity management, and roadmap execution, balancing feature velocity with technical debt reduction
• Drive a culture of engineering rigor: automated testing, CI/CD maturity, observability, and incident response
• Define, track, and report on delivery metrics (cycle time, defect rates, deployment frequency) using data-driven approaches
• Manage competing priorities with transparency, proactively communicating risks and trade-offs to stakeholders
• Develops operational plans for the group based on broader engineering and corporate strategy; strategic decisions have a 2-4 year impact horizon
• Lead by example in the evaluation, piloting, and scaled rollout of generative AI tools for code generation, test automation, documentation, and developer workflows
• Define best practices and guardrails for responsible GenAI use within the software development lifecycle (SDLC), including security, IP, and compliance considerations
• Partner with platform and DevOps teams to integrate AI tooling into CI/CD pipelines and developer environments
• Measure and communicate the ROI of GenAI adoption through productivity metrics and developer experience surveys
• Act as an internal evangelist for AI-augmented engineering, educating teams, leadership, and stakeholders on capabilities and responsible use
• Serve as the primary engineering point of contact for product, design, security, and customer success teams
• Collaborate with architects, platform engineering, and other group managers to drive consistency in technology choices, shared services, and reusable components
• Engage with customers and partners when needed to understand technical requirements and provide confidence in engineering capabilities
• Represent the engineering team in executive reviews, quarterly planning, and cross-functional forums
• Ensure software development practices comply with enterprise security standards and relevant regulatory requirements (e.g., SOC 2, HIPAA where applicable)
• Instill quality engineering practices: code coverage standards, static analysis, security scanning, and vulnerability management within the SDLC
• Partner with QA and security teams to define and enforce quality gates across the delivery pipeline

Requirements:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field
• Equivalent practical experience in lieu of formal education will be considered
• 10+ years of software engineering experience, including 5+ years in an engineering management or technical lead role
• 5+ years of experience managing teams of 8 or more engineers in an enterprise SaaS company
• Demonstrated experience driving the adoption of generative AI tooling within a software development team
• Background in building and shipping enterprise software products with high reliability, security, and scalability requirements
• Experience working in regulated or compliance-sensitive industries (healthcare IT, fintech, or similar) is a plus