Engineering Manager, Customer Tools

Role details

MongoDB is seeking an Engineering Manager to lead a team of software engineers responsible for developing and maintaining the applications and platforms that power our Customer organization. From scoping and design, through implementation, deployment and monitoring, the Customer Tools team builds the systems that make our customer-facing teams successful — internal dashboards, workflow automation, data and diagnostics platforms, and a growing suite of AI-powered capabilities. This role has two closely linked mandates: modernizing how the team itself builds software by adopting AI-assisted engineering workflows, and shipping AI-native features — chat interfaces, automated analyses, and proactive insights — directly to end users across the Customer organization. The ideal candidate brings a strong technical background, hands-on familiarity with modern AI/LLM tooling, and experience managing multi-functional teams of engineers. While this role is focused on managing the team itself, a strong technical background will help provide necessary context for the work and motivations of the team. We are looking to speak to candidates who are based in Mexico City for our hybrid working model. Candidate Profile 10+ years of professional experience, including: 5+ years of experience managing teams of software engineers. This includes people-management responsibilities such as hiring, performance and growth management, compensation planning, and career development 5+ years providing technical leadership to development teams, including project scoping and design, leading code reviews, driving best practices, providing architectural guidance, and managing technical stakeholders 5+ years of hands-on experience building scalable high-availability systems and integrations Experience working with modern web technologies and infrastructure stacks, such as TypeScript, ReactJS, Python, AWS services, GitHub, Claude Code, Cursor, etc Genuine enthusiasm for AI-assisted software development — you've used tools like Claude Code, Copilot, Cursor, or similar in your own workflow and have a point of view on how they change engineering practice Experience building or shipping AI-powered product features (e.g., chat/conversational interfaces, LLM-driven analyses, recommendation or insight engines) is a strong plus Understanding of agile software development methodologies and test-driven development Deep experience in software engineering management with a track record of effectively balancing short-term needs with long-term strategic investment Experience managing multiple stakeholders and external vendors and can clearly articulate risks and dependencies on projects Passion for data-related services and understanding of good systems design Experience building platforms or tools where the main users are internal customers (technical and non-technical) or customer-facing teams You care about facilitating learning and growth on the team – you put our engineers first You lead the team to explore all potential paths to a solution, while accepting that failure is part of the process You're comfortable operating at the intersection of "how we build" and "what we build" — championing AI adoption in engineering process while also shipping AI in the product Position Expectations Manage a team of 8-10 individual contributors, responsible for ensuring their success, aiding their career growth, and facilitating their technical work Drive adoption of AI-assisted engineering workflows across the team — code generation, review, testing, and documentation — to increase velocity and quality. The goal is to empower software engineers with AI to help the team scale Own the roadmap for AI-powered end-user features, including chat-based interfaces, automated analyses, and insights that help customer-facing teams work more effectively Ensure the team is running smoothly by helping to eliminate technical barriers, coordinating with other teams regarding dependencies, and focusing on the overall happiness of the team Contribute to planning for organizational growth, including allocation of engineering resources, future hiring plans, and assignment of projects Set team culture by example, including modeling a thoughtful, hands-on approach to evaluating and adopting new AI tools and practices Estimate the delivery timeline for projects, and communicate well with upper management and the broader team regarding project execution Success Measures The Manager will be successful in this role when they can execute the following strategic tasks: People: Collaborate with colleagues from various departments and manage stakeholder relationships. Participate in the performance management process and define meaningful growth goals for individual engineers. Establish reasonable metrics for measuring performance improvements across the team Organization: Ability to manage multiple parallel efforts and prioritize resources based upon understanding and interpreting business needs Communication: Effectively capture requirements from non-technical customers and ensure they understand the implementation details. Provide transparency on delivery and process Research: Research best approaches to implementing workflows — including AI-assisted engineering practices — that enable our business. Gather and analyze feedback from internal stakeholders Innovation: Identify and evaluate opportunities to apply AI to both the team's engineering workflows and the products it ships, moving from experimentation to production responsibly Customer Service: Provide pragmatic solutions for our internal stakeholders. Provide great customer service when interfacing with internal customers About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely a