Sr. Manager- Software Engineering- Healthcare IT

Merative•Mississauga, ON

9d•CA$156,982 - CA$235,473•Remote

About The Position

Merge medical imaging solutions, offered by Merative, combine intelligent, scalable imaging workflow tools with deep and broad expertise to help healthcare organizations improve their confidence in patient outcomes and optimize care delivery. We are seeking a proven and forward-thinking Sr. Manager, Software Engineering to lead a team of 10–15 software engineers delivering enterprise SaaS solutions. This role is central to driving technical excellence, developer productivity, and the thoughtful adoption of AI-assisted development practices across the engineering organization. The Sr. Manager will balance hands-on technical leadership with strategic people management—coaching engineers, partnering cross-functionally, and ensuring the team delivers high-quality software at scale. The ideal candidate brings deep experience in enterprise software development, a genuine enthusiasm for generative AI tooling, and a track record of building collaborative, high-performing teams. This role is remote and open for both U.S and Canada.

Requirements

Proven ability to lead and grow high-performing software engineering teams in an enterprise SaaS environment.
Deep technical credibility. Engineers trust your judgment on architecture, tooling, and design decisions.
Demonstrated hands-on experience adopting and championing generative AI tools within a software development team.
Strong product mindset with the ability to align engineering work to business outcomes and customer value.
Exceptional communication skills: able to articulate technical complexity to non-technical audiences and vice versa.
Data-driven decision maker with experience using engineering metrics to drive continuous improvement.
Collaborative leader who thrives in cross-functional, fast-paced environments with shifting priorities.
Proficiency in one or more enterprise-grade programming languages and frameworks (e.g., Java, Python, Node.js, React, Go).
Hands-on experience with generative AI coding tools (GitHub Copilot, Claude Code) and AI-assisted testing/documentation pipelines.
Solid understanding of cloud-native development on AWS, Azure, or GCP; familiarity with containerization (Docker, Kubernetes) and serverless architectures.
Experience with CI/CD pipelines, DevOps practices, and modern build/deploy tooling (GitHub Actions, Jenkins, ArgoCD, etc.).
Familiarity with microservices architecture, API design (REST, GraphQL), and distributed systems patterns.
Working knowledge of security best practices within the SDLC, including OWASP, SAST/DAST tooling, and secrets management.
Proficient with engineering productivity and observability tooling (Jira, Datadog, Splunk, PagerDuty, or equivalents).
Experienced people manager with a track record of developing engineers at all levels, including senior and staff-level contributors.
Skilled at navigating performance management, compensation conversations, and career pathing in a structured, equitable manner.
Ability to build team cohesion and maintain morale through periods of organizational change, ambiguity, or high delivery pressure.
Experience managing in a globally distributed or remote-first engineering environment.
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.

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.
Ensure 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.