Software Engineering Manager

Merck•Burlington, MA

3d•Hybrid

About The Position

We are seeking an AI-native, highly hands-on Software Engineering Manager to lead engineering efforts across the full software development lifecycle (SDLC)—from solution design and coding through deployment, production support, and continuous improvement. The role has a high hands-on engineering focus, including designing, coding, testing, reviewing, deploying, and operating production software. It also includes technical leadership, team development, prioritization, and stakeholder collaboration. The ideal candidate uses AI as a core part of their engineering workflow while maintaining accountability for quality, security, and production outcomes. Experience in the life sciences, pharmaceutical, biotechnology, healthcare, or another regulated environment is preferred.

Requirements

Bachelor's Degree in Computer Science, Software Engineering, or equivalent practical experience.
Proven experience delivering software applications to production.
Strong hands-on software development experience across the SDLC.
Experience leading engineering teams, initiatives, or technical delivery.
Strong knowledge of Git, GitHub, CI/CD, and GitHub Actions.
Practical experience designing and operating solutions on AWS.
Experience using AI-assisted development tools such as Claude and GitHub Copilot.
Strong understanding of automated testing, secure development, APIs, observability, and system reliability.
Excellent communication, collaboration, and mentoring skills.

Nice To Haves

Experience in life sciences or a regulated industry.
Familiarity with software validation, data integrity, auditability, privacy, or computer system assurance.
Experience with containers, serverless or event-driven architectures, infrastructure as code, and application security.
Experience working in agile, product-oriented, or DevOps environments.

Responsibilities

Spend approximately 50–60% of time hands-on, contributing directly to architecture, coding, testing, code reviews, deployments, troubleshooting, and production support.
Lead software engineering initiatives from concept through production delivery.
Guide teams across the SDLC and establish effective engineering practices for quality, security, reliability, and maintainability.
Design, deploy, and operate cloud-based solutions on AWS.
Build and maintain CI/CD pipelines and automated delivery workflows using GitHub Actions.
Improve application observability, performance, security, and operational readiness.
Work in an AI-native manner, using tools such as Claude and GitHub Copilot as an integral part of daily engineering work, including development, testing, refactoring, documentation, and problem-solving.
Define effective practices for reviewing and validating AI-generated code for quality, security, compliance, and maintainability.
Mentor engineers, provide technical direction, and collaborate with product, architecture, security, and business stakeholders.
Identify technical risks and continuously improve development and delivery processes.