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MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently. As the Site Reliability Engineering Manager for SLS, you will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll help grow and lead a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture. We are looking to speak to candidates who are based in Cork for our hybrid working model. Responsibilities Build and lead a team of 6-8 engineers, fostering a positive culture, handling career growth and performance conversations, and proactively removing blockers Define and drive a clear technical vision and comprehensive roadmap for our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs Contribute through hands-on technical work, such as leading architectural design reviews, reviewing PRs, and stepping in to guide the team through complex operational challenges Act as the primary liaison for the Storage Layer Services SRE team, collaborating closely with other engineering leaders to ensure platform alignment and manage stakeholder expectations You may be a good fit if you Have 10+ years of experience working on software and operating distributed systems, with 2+ years managing engineering teams Possess a customer-focused mindset, treating internal developers as your primary users Value efficiency in processes and operations, and have a track record of optimizing team workflows Prefer automation over manual processes, fostering a culture of building software solutions to eliminate toil Have deep technical familiarity with Kubernetes ecosystems, containerization technologies, and modern IaC tooling (e.g., Terraform, Crossplane, or Operators) so you can effectively guide the team's technical decisions Have operated or supported stateful storage or database systems at scale and are comfortable with durability, consistency and recovery trade-offs Excel at translating complex business and engineering requirements into actionable, phased technical roadmaps Have a high level of empathy, responsibility, ownership, and accountability Excellent verbal and written technical communication skills Strong candidates may also have experience with Leading major architectural shifts, such as moving from legacy storage stacks to new multi-tenant storage architectures, including planning and executing large-scale data and workload migrations with tight availability and durability requirements Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure) Designing secure, multi-tenant runtime environments at scale 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 available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Req ID: 1273396229

Application Modernization Platform (“AMP”) is a MongoDB offering that modernises our customer’s legacy relational applications to a modern architecture underpinned by MongoDB using a combination of software, processes, and engineers. In this offering, the people and software are inextricably linked and cannot be separated. The delivery happens in an accelerated timeframe wherein the team takes advantage of GenAI and algorithmic tooling to expedite the turnaround time for application delivery. AMP team generally works with enterprise-grade customers, in all verticals on a variety of exciting use cases. This role solves technically sophisticated problems, gains incredible cross-stack experience, works with top-notch people in the business, addresses multiple customer-facing opportunities. The role also becomes the forefront of groundbreaking R&D that enables further acceleration for enterprises working across a variety of technologies. AMP exists to expedite time to value for customers who are looking forward to changing, modernising and updating their tech stack while keeping MongoDB the cornerstone of their system architecture. Work as a software developer in an Agile environment delivering solutions for customers focused on migrating our customers’ legacy relational-based Java applications to a more modern cloud-based architecture running on MongoDB, leveraging the latest GenAI tools and approaches to accelerate this process. During each project, successful candidates will be required to innovate on potential new GenAI-based solutions for specific challenges in addition to applying existing playbooks and tooling for migration. This role will be based remotely in France. Position Expectations Shape architecture and technology strategy across AMP modernization projects and workstreams, making complex technical decisions with limited supervision and connecting engineering choices to customer and business outcomes Lead the assessment and modernization of legacy Java applications by uncovering dependencies, embedded business logic, integration points, and operational constraints; recommend fit-for-purpose modernization paths rather than defaulting to lift-and-shift Design, implement, and review production-quality solutions using Java and Spring Boot, including APIs, integrations, monolith decomposition, relational-to-document data modeling, stored-procedure transformation, schema evolution, and MongoDB operational practices Establish safe, incremental delivery practices through explicit acceptance criteria, automated testing, CI/CD, observability, and rollback, dual-run, or other risk-control strategies; identify quality, security, performance, and reliability risks and guide teams to resolve them Serve as a senior technical partner to customers, application owners, and account and project stakeholders by explaining complex topics clearly, aligning priorities, navigating disagreement, communicating trade-offs, and maintaining trust through high-risk change Multiply the effectiveness of engineers by mentoring, raising engineering standards, creating reusable migration playbooks and documentation, applying GenAI advancements responsibly where valuable, and influencing project direction without relying on formal authority Requirements Professional fluency in French is required Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience Typically 8+ years of progressive experience designing, building, and delivering Java applications, including significant experience leading complex application modernization initiatives Expert understanding of Java fundamentals, object-oriented design, concurrency, error handling, performance considerations, and maintainable software architecture; able to review code and guide design decisions across teams Deep production experience with Spring Boot and related patterns for building resilient services, APIs, integrations, and testable distributed applications Demonstrated ability to assess legacy estates, decompose monoliths, uncover dependencies and embedded business logic, and define practical modernization strategies with clear trade-offs Strong experience with relational databases and SQL, including stored procedures, data dependencies, data migration, schema evolution, and relational-to-document modeling for MongoDB or comparable document databases Proven history of delivering high-cadence modern applications using Agile methodologies, test-first development, CI/CD pipelines, Git-based version control, observability, and reliability practices; demonstrated success mentoring engineers and influencing technical outcomes across teams Nice-to-have skills Experience in building REST APIs with Spring Boot Experience in performance and memory optimization of JAVA applications Familiarity with tools like Postman, IntelliJ IDEA, and Maven/Gradle Exposure to other languages or technologies like JavaScript, .Net Understanding of ORM tools like Hibernate, Spring Data or JPA (even through coursework or self-study) Experience in nascent GenAI technologies and approaches, such as using OpenAI/Anthropic API not purely through chat interfaces Experience with AI-powered development tools like Claude Code, Cursor, or similar code assistants Good experience of using MongoDB Successful candidates will engage with customer systems and may be exposed to highly confidential customer data, including but not limited to non-public information. For this reason, and due to the nature of the highly regulated industry in which our customers operate, successful candidates may be subject to enhanced background checks, security screenings, and possible constraints around the trading of securities. Successful candidates will understand these requirements and be willing to participate in enhanced screenings and constraints as required by MongoDB and its customers in connection with this role. 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 available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Req ID: 3273528270

This role can be based remotely in India. Position Summary We are seeking an exceptional Principal Technologist to join our team in India. This pivotal role will work closely with our account teams to engage with C-suite executives and senior technical leaders at MongoDB’s most strategic customers. You will bridge the gap between complex data architectures and AI to power business transformation, positioning MongoDB as the premier platform for modernizing legacy systems and building next-generation AI applications. As a recognized technical thought leader, you will shape industry perspectives through regular activities including high-impact technical evangelism and thought leadership, executive roundtables, presentations delivered to customers, keynotes at MongoDB and industry events, and regularly briefing tier-1 press, media, and analysts as a credible and trusted company spokesperson. Qualifications 10+ years of experience in customer and market-facing roles at the principal or Field CTO level Recognized technical leader with deep hands-on experience with enterprise-scale applications Influence & Scalability: Demonstrated success in scaling your technical influence and earned credibility. Experience speaking at major tech conferences, hosting technical webinars, or contributing deeply to the developer community (via technical blogs, open-source contributions, or whitepapers) is highly desired Deep portfolio and history of published content, presentations at events, interviews or quotes in the the press and media Executive Presence: Exceptional ability to command a room with credibility, deliver compelling keynote presentations, and influence technology strategies with a CxO audience Strong understanding of database architectures, distributed systems, and cloud computing concepts, with experience in distributed systems design, including scalability, fault tolerance, and consistency models Familiarity with modern application development frameworks and hands-on proficiency with state of the art AI capabilities Bachelor's or advanced degree in Computer Science, Engineering, or related field, or equivalent experience What We Offer Extensive travel (up to 50%) may be required, but can be offset by a strong existing digital footprint and community influence within the region Ability to exert broad industry influence and build your personal brand The chance to go deep on MongoDB, learning the most successful next generation database platform and seeing first-hand how the world's biggest companies use it for their most demanding applications Opportunity to influence technical direction and strategic decisions and some of the world's largest companies Competitive salary and benefits package Focused, high-performing team and close collaboration with your peers across the organization 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 database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. REQ ID: 4253000823

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improvements to fleet stability, efficiency, or operational automation; deepened working relationships with two or more partner engineering teams; and become a go-to resource for statistical or engineering rigor across the team Skills & Attributes 5+ years of hands-on machine learning model development, working directly with technical stakeholders Expertise and track of record working autonomously across the entire machine learning development lifecycle, including prototyping, simulation, tuning and iterating on products in deployment environments with and without dedicated engineering help Embraces an object-oriented approach to designing scalable and readable Python codebase, and has experience working with engineers on architecture design of machine learning systems Our codebase is primarily in Python and we use AI for developer productivity - but we expect all ICs to review, understand, and be able to redesign any code that ships regardless of whether a human or an AI wrote the first draft Takes ownership of team culture: models psychological safety, and - in whatever way suits their style, whether that's a quiet word or a vocal challenge - encourages others to speak up and calls out when the environment isn't living up to it Effective at communicating technical ML concepts to non-ML-experts audiences; e.g. able to translate efficacy measurements of ML models and products into tangible business impact metrics Master's degree or equivalent experience in a quantitative/computational discipline (computer science, applied mathematics, statistics, physics, operations research, etc.) 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 available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Req ID: 3273521781

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improvements to fleet stability, efficiency, or operational automation; deepened working relationships with two or more partner engineering teams; and become a go-to resource for statistical or engineering rigor across the team Skills & Attributes 5+ years of hands-on machine learning model development, working directly with technical stakeholders Expertise and track of record working autonomously across the entire machine learning development lifecycle, including prototyping, simulation, tuning and iterating on products in deployment environments with and without dedicated engineering help Embraces an object-oriented approach to designing scalable and readable Python codebase, and has experience working with engineers on architecture design of machine learning systems Our codebase is primarily in Python and we use AI for developer productivity - but we expect all ICs to review, understand, and be able to redesign any code that ships regardless of whether a human or an AI wrote the first draft Takes ownership of team culture: models psychological safety, and - in whatever way suits their style, whether that's a quiet word or a vocal challenge - encourages others to speak up and calls out when the environment isn't living up to it Effective at communicating technical ML concepts to non-ML-experts audiences; e.g. able to translate efficacy measurements of ML models and products into tangible business impact metrics Master's degree or equivalent experience in a quantitative/computational discipline (computer science, applied mathematics, statistics, physics, operations research, etc.) 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 available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Req ID: 3273521781