Senior Engineering Manager, Core Media & Intelligence

Dropbox is a global community shaping the future of work through innovative cloud-based solutions. The Senior Engineering Manager will lead a team responsible for integrating AI capabilities into Dropbox’s File Sync & Share product, driving impactful results in a collaborative environment.

Responsibilities:

• Directly manage up to 20 direct reports, as a single execution unit
• Partner with multiple Product Managers to plan roadmaps and sprints
• Be accountable for high quality execution on critical and high visibility business objectives
• Be responsible for making tradeoffs between feature work and addressing long term technical debt
• Be responsible for excellence in software quality, engineering practices and operations
• Lead the team through standard Agile processes, such as backlog management, stand ups, retros, etc
• Review and approve engineering designs and be able to set technical direction (in collaboration with a Technical Lead)
• Drive cross-org initiatives alongside managing execution responsibilities
• Drive career conversations and career plans for your direct reports

Requirements:

• BS, MS, or PhD in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent technical experience
• Minimum of 8 years of people management experience with an engineering team
• Minimum of 10 years as a software engineer or equivalent technical experience
• Must have experience managing engineering organizations of 20 or above and experience managing managers
• Must have experience building or integrating with AI products
• Must have worked in a platform team or a developer-facing API product with both internal and external consumers
• Must have experience running a standard Agile process such as backlog management, stand ups, retros, etc
• Must be results-driven, especially good at balancing execution predictability with the agility needed in bringing a new product to market
• Experience shipping AI-powered features in production, collaborating closely with ML engineers and product teams
• Strong backend engineering skills with systems that support model serving, inference, and data pipelines at scale
• Strong background in AI agent infrastructure and building AI agents
• Ability to evaluate AI models for a specific use case and advise on build vs buy decisions
• Expertise in distributed systems architecture — designing for scalability, fault tolerance, observability, and graceful degradation in multi-service environments