Sr Mgr, Amazon Science Engineering, Academic Research Initiatives & Science Community

About the role

The ARI-SciCom Engineering team builds and operates the software platform that powers scientific publishing and research collaboration across Amazon. Our tools support the full lifecycle of scientific communication — from paper authoring and approval through conference management and research impact assessment and an innovator database containing hundreds of thousands of researchers, their institutions, and their projects. Our tools accelerate innovation for a community of 10K+ Amazon scientists and 20K+ research collaborators. We sit at the intersection of engineering, science, and AI: Building the infrastructure that enables Amazon’s scientists to discover, share, and amplify their work. The team is trusted with both operational excellence on mission-critical systems and bold innovation on next-generation AI tooling.

Responsibilities

• Own the technical vision and execution for a portfolio of tools that directly enable scientific discovery and collaboration at Amazon scale.
• Balance operational excellence on existing systems with ambitious product development on AI-powered tools that will transform how Amazon supports its rapidly evolving science community.
• Manage a team of software development engineers, set technical direction, drive roadmap prioritization, and partner closely with science leadership, and internal conference organizers.
• Think big about how AI and automation can accelerate scientific productivity while delivering incremental value through disciplined execution and bar-raising engineering standards.

Requirements

• 10+ years of engineering experience
• 5+ years of engineering team management experience
• Experience managing multiple concurrent programs, projects and development teams in an Agile environment
• Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
• Proficiency with AI development methodologies, modern CI/CD practices, and engineering operational excellence.

Qualifications

• Master's degree or above in computer science, machine learning, engineering, or related fields, or PhD
• Hands-on experience building AI/ML-powered products or integrating large language models into production workflows
• Familiarity with scientific publishing workflows, academic conference management, or research administration systems
• Demonstrated ability to work effectively with non-engineering stakeholders — scientists, researchers, and program managers — translating ambiguous domain needs into clear engineering requirements

Skills

• Strong leadership skills
• Experience with Agile methodologies
• Experience with large-scale software development and deployment
• Experience with AI/ML development and integration
• Experience with scientific publishing and conference management systems

Benefits

• Comprehensive benefits including medical, dental, vision, prescription, life insurance, AD&D, EAP, mental health support, flexible spending accounts, adoption and surrogacy reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave