Careers at MongoDB

The MongoDB Developer Tools team is a diverse group of contributors working together to help our users manage MongoDB at global scale. This includes building tools for MongoDB Atlas: our database as a service offering and fastest growing product which allows users to deploy fault-tolerant, globally distributed MongoDB clusters in just minutes. We're seeking an experienced Software Engineer to join our Developer Tools Team within the Database Experience department. The team is responsible for tools which allow users to interact with their data and to understand the health and performance of their MongoDB deployments. The Developer Tools Team works on a variety of APIs and customer-facing UIs empowering MongoDB users to interact with their stored data, whether that’s on desktop via MongoDB Compass or in the browser via Atlas Data Explorer. This role is fully remote for a candidate based in the United States with US citizenship. We're looking for someone who Is a full stack engineer with a willingness to take on both frontend tasks and backend tasks Experience working with TypeScript, React, and Node.js Has experience with the design and architecture of a modern, scalable, high availability web application Has experience working with databases Enjoys collaboration and being part of a team Is approachable, curious, and intellectually honest Would enjoy chasing down difficult problems in a distributed environment Always strives to expand their knowledge Nice to Haves Knowledge of database internals and tuning mechanisms, particularly indexing Experience working with websocket based client to server communication Familiarity with developing and supporting microservice based architectures using Kubernetes 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Req ID: 2273494846 MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates. MongoDB’s base salary range for this role in the U.S. is: $106,000 — $209,000 USD

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's structured result when item order may vary, but counts, required fields, and values must remain correct How can a CI gate flag unsafe instructions in an agent skill without treating every neutral mention as an incident or letting cautionary wording hide a real instruction How can an evaluation suite show whether a skill improves answers over a baseline and give authors enough signal to improve it What we're looking for 2+ years of experience building production software, developer tools, internal platforms, or automation systems Software engineering fundamentals in API design, testing, error handling, and maintainability Experience building CLIs, libraries, test infrastructure, static analysis, or CI/CD workflows Ability to design systems that are usable by developers and reliable in automation Experience reasoning about correctness and safety with ambiguous input, nondeterministic output, false positives, or untrusted content Comfort in an evolving R&D environment where the right abstraction emerges through prototypes and feedback Written and verbal communication, including explaining technical trade-offs and aligning stakeholders across teams Nice to have Experience with agentic systems, LLM applications, prompt or rubric-based evaluation, or AI-assisted development Experience building eval harnesses, benchmark datasets, quality metrics, LLM-as-judge workflows, or human-review tooling Experience with Go, Python, JavaScript/TypeScript, Java, or C# Experience with GitHub Actions security, secret handling, static rule engines, or policy enforcement Experience moving prototypes into production What success looks like In your first year, you will: Ship tooling that makes agent skills or developer workflows easier to test, review, and adopt Improve the quality and interpretability of evaluations, not just their count Convert recurring manual work and fragile scripts into documented, reusable automation Make security, correctness, and operational trade-offs explicit in the designs you ship Earn adoption from partner teams through clear interfaces and reliable CI Own projects independently while collaborating on shared systems 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. Red ID: 2273504602 AI is used to review applications based on job-related criteria and does not replace human decision-making. The hiring team decide who moves forward. MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, Registered Retirement Savings Plan (RRSP) with employer match, mental health counseling, backup child and elder care, and health, dental, and vision benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to candidates based in Canada. MongoDB’s base salary range for this role in Canada is: $108,000 — $149,000 CAD

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's structured result when item order may vary, but counts, required fields, and values must remain correct How can a CI gate flag unsafe instructions in an agent skill without treating every neutral mention as an incident or letting cautionary wording hide a real instruction How can an evaluation suite show whether a skill improves answers over a baseline and give authors enough signal to improve it What we're looking for 2+ years of experience building production software, developer tools, internal platforms, or automation systems Software engineering fundamentals in API design, testing, error handling, and maintainability Experience building CLIs, libraries, test infrastructure, static analysis, or CI/CD workflows Ability to design systems that are usable by developers and reliable in automation Experience reasoning about correctness and safety with ambiguous input, nondeterministic output, false positives, or untrusted content Comfort in an evolving R&D environment where the right abstraction emerges through prototypes and feedback Written and verbal communication, including explaining technical trade-offs and aligning stakeholders across teams Nice to have Experience with agentic systems, LLM applications, prompt or rubric-based evaluation, or AI-assisted development Experience building eval harnesses, benchmark datasets, quality metrics, LLM-as-judge workflows, or human-review tooling Experience with Go, Python, JavaScript/TypeScript, Java, or C# Experience with GitHub Actions security, secret handling, static rule engines, or policy enforcement Experience moving prototypes into production What success looks like In your first year, you will: Ship tooling that makes agent skills or developer workflows easier to test, review, and adopt Improve the quality and interpretability of evaluations, not just their count Convert recurring manual work and fragile scripts into documented, reusable automation Make security, correctness, and operational trade-offs explicit in the designs you ship Earn adoption from partner teams through clear interfaces and reliable CI Own projects independently while collaborating on shared systems 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Red ID: 2273504602 MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates. MongoDB’s base salary range for this role in the U.S. is: $109,000 — $215,000 USD

The Application Modernization Platform (AMP) team is dedicated to solving one of the industry's biggest challenges: transforming rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures on MongoDB. To accelerate this transition, MongoDB is building a dedicated Platform and Infrastructure team to develop the Application Modernisation Platform and Infrastructure . As we help customers modernize their application and data ecosystems, we face the challenge of deploying complex tooling into highly restrictive client environments and architecting automated verification frameworks to ensure data equivalence. This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage data and AI. We are looking for an experienced Software Engineer who thrives on solving infrastructure constraints and building developer-centric modernisation platforms with a strong background in building software testkits/frameworks. The ideal candidate will be designing and building automated frameworks that validate functional equivalence, performance benchmarks, and data integrity. From leveraging LLMs for unit test generation to building contract testing frameworks, your work will be the safety net for the world’s largest enterprise migrations. This role will be based in our India office in Gurgaon and offers a hybrid working model. The ideal candidate for this role will have 3-4 years of commercial software development experience with at least one JVM language such as Java, preferably using the Spring ecosystem. Expertise integrating Large Language Models (LLMs) into the developer workflow to automate unit test generation and edge-case discovery. Experience building developer tools, infrastructure, or complex testing frameworks. Solid experience in software architecture and development. Deep expertise in application/database modernization with proven ability to design and implement frameworks that ensure database state equivalence across different implementations. Must understand change data capture, event-driven database interception (MongoDB listeners, RDBMS triggers), and state comparison algorithms with pattern-based exclusions. Strong Spring Boot (or equivalent Java framework), MongoDB (or equivalent), and JDBC/JPA skills required. Extensive experience with relational and document data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) and at least one document database (e.g. MongoDB). Good understanding of algorithms, data structures and their time and space complexity. Curiosity, a positive attitude, and a drive to continue learning. Excellent verbal and written communication skills. Position Expectations Contribute high-quality, well-tested code to the modernization and framework team and its surrounding services. Collaborate effectively with Product Management, other engineers, and designers to build and deliver on the product roadmap. Participate actively in code reviews to enforce best practices and patterns. Help troubleshoot and resolve complex technical issues in our distributed systems. Give and solicit feedback on technical design documents and pull requests Perform tasks related to process such as CI/CD, quality, testing, etc Success Measures Within the first three months, you will have: Familiarize yourself with the MongoDB Modernization Infrastructure & Frameworks stack. Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks Started collaborating with your peers and contributed to code reviews and design reviews. Within six months, you will have: Familiarised yourself with the rest of our the application modernization tool stack Delivered at least one large scale feature that spans the entire tech stack Reviewed and contributed to scope and technical design documents Within 12 months, you will have: Become a key contributor to our stack, capable of taking on complex features independently. Helped recruit and interview new members of the team Collaborated effectively with other teams at MongoDB on cross-functional projects 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. Requisition ID- 3273534560

The Application Modernization Platform (AMP) team is dedicated to solving one of the industry's biggest challenges: transforming rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures on MongoDB. To accelerate this transition, MongoDB is building a dedicated Platform and Infrastructure team to develop the Application Modernisation Platform and Infrastructure . As we help customers modernize their application and data ecosystems, we face the challenge of deploying complex tooling into highly restrictive client environments and architecting automated verification frameworks to ensure data equivalence. This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage data and AI. We are looking for an experienced Software Engineer who thrives on solving infrastructure constraints and building developer-centric modernisation platforms with a strong background in building software testkits/frameworks. The ideal candidate will be designing and building automated frameworks that validate functional equivalence, performance benchmarks, and data integrity. From leveraging LLMs for unit test generation to building contract testing frameworks, your work will be the safety net for the world’s largest enterprise migrations. This role will be based in our India office in Gurgaon and offers a hybrid working model. The ideal candidate for this role will have 3-4 years of commercial software development experience with at least one JVM language such as Java, preferably using the Spring ecosystem. Expertise integrating Large Language Models (LLMs) into the developer workflow to automate unit test generation and edge-case discovery. Experience building developer tools, infrastructure, or complex testing frameworks. Solid experience in software architecture and development. Deep expertise in application/database modernization with proven ability to design and implement frameworks that ensure database state equivalence across different implementations. Must understand change data capture, event-driven database interception (MongoDB listeners, RDBMS triggers), and state comparison algorithms with pattern-based exclusions. Strong Spring Boot (or equivalent Java framework), MongoDB (or equivalent), and JDBC/JPA skills required. Extensive experience with relational and document data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) and at least one document database (e.g. MongoDB). Good understanding of algorithms, data structures and their time and space complexity. Curiosity, a positive attitude, and a drive to continue learning. Excellent verbal and written communication skills. Position Expectations Contribute high-quality, well-tested code to the modernization and framework team and its surrounding services. Collaborate effectively with Product Management, other engineers, and designers to build and deliver on the product roadmap. Participate actively in code reviews to enforce best practices and patterns. Help troubleshoot and resolve complex technical issues in our distributed systems. Give and solicit feedback on technical design documents and pull requests Perform tasks related to process such as CI/CD, quality, testing, etc Success Measures Within the first three months, you will have: Familiarize yourself with the MongoDB Modernization Infrastructure & Frameworks stack. Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks Started collaborating with your peers and contributed to code reviews and design reviews. Within six months, you will have: Familiarised yourself with the rest of our the application modernization tool stack Delivered at least one large scale feature that spans the entire tech stack Reviewed and contributed to scope and technical design documents Within 12 months, you will have: Become a key contributor to our stack, capable of taking on complex features independently. Helped recruit and interview new members of the team Collaborated effectively with other teams at MongoDB on cross-functional projects 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 - 3273532211

MongoDB seeks an experienced Software Engineer to join Enterprise Architecture on a focused team dedicated to AI experimentation. You'll partner with teams across the organization, including Internal Engineering, to explore, prototype, and validate emerging AI capabilities before they become formal roadmap priorities. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Our ideal candidate: Has 2-5 years of professional software engineering experience Deep experience with at least one modern programming language (Python, Typescript, Go, Rust, etc.) Strong technical judgment and the ability to independently solve complex engineering problems Excellent communication skills and comfort collaborating across teams and disciplines Comfortable operating in ambiguity, scoping and running experiments when the right approach isn't known yet Hands-on experience prototyping with LLMs or agentic systems (evals, fine-tuning, RAG, tool use, orchestration frameworks) Has the ability to iterate fast, specially in the case where requirements are not clear Keeps up with emerging AI tooling and models, not just what's already mainstream Collaborative, detail-oriented, and passionate about developing usable software Bonus Round: Experience building and maintaining full-stack applications, from front-end UIs to backend API to data pipelines Experience designing systems or services used by other engineers or teams Knowledge of any of the following technologies: Tanstack Start, Next.js, FastAPI, React Experience with model evaluation frameworks, vector databases, or agent orchestration tooling (e.g., LangGraph) Familiarity with transformer architecture and model internals Familiarity with containerized applications, Kubernetes, and ability to design CI/CD pipelines Position Expectations: Design and run experiments that test emerging AI capabilities against real internal use cases, before they're formally prioritized. Condense the learnings of those experiments and document them so that the knowledge can be used across the org. Build lightweight prototypes to validate or kill ideas quickly Stay current on new AI tooling and models, and turn relevant developments into concrete internal proof points Partner with product, platform, and internal engineering teams to hand off validated capabilities once they're ready to move from experiment to production Maintain technical rigor and clear documentation of findings, even for work that doesn't ship Identify and communicate risks, unknowns, and open questions clearly to stakeholders Success Measures: In three months, have run and documented at least one AI capability experiment, with a clear recommendation on whether and how to pursue it further In three months, demonstrate the ability to move quickly from idea to working prototype In six months, have influenced the org's roadmap or tooling direction by surfacing a capability two to three steps ahead of current need, backed by evidence from your experimentation 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. Requisition ID - 3273558097

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

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 Dublin 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

Come join and lead the Server Ingress Security team, where we are rearchitecting MongoDB Server’s ingress networking to make MongoDB clusters even more secure. This new team is building the Atlas Network Protection layer, a set of performant, security-critical services that harden MongoDB's pre-authentication attack surface and provides the ability to respond rapidly to emergent threats. We are looking for a talented Lead Engineer to join the team and be founding members, where you will play a crucial role in our multi-year roadmap. Our team champions a strong culture of inclusivity, diversity, and collaboration, and lives MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. If you want to lead a fast-growing team that applies security and systems engineering fundamentals to protect a popular database at scale, join us! We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 3+ years of experience managing a team of software engineers, including hiring, performance and growth management, compensation planning, and mentoring You have 8+ years of experience building production-quality systems software with large backend/compiled codebases, ideally in Rust. Bonus points for experience with performance profiling, network protocols, TLS, and connection management You have strong technical judgment that you use to effectively guide engineering decisions in security-sensitive or networking-adjacent domains You put the customer first and don't hesitate to cross team boundaries in search of the right solution Solid experience in designing, writing, testing, maintaining, and operating mission-critical software systems Bonus points Professional or advanced academic expertise in the domains of security or networking You enjoy coaching, career development, and creating growth opportunities to help your team reach their full potential You care about building a diverse, inclusive environment where engineers can do their best work Regardless of prior experience, you are willing, able, and excited to quickly learn new things in the domains of computer science, software engineering, and leadership Position Expectations Lead a team of engineers, managing all aspects of people management including hiring, growth, compensation, and performance management Be directly responsible for the results your team delivers Lead the design, implementation, and operation production-ready security services in Rust, with a focus on security, correctness, performance, and operational excellence Own the definition and execution of the team's 12-month roadmap for the Atlas Network Protection layer Work with Product Management, Program Management, and Engineering leadership to specify, prioritize, and deliver new features Handle (or lead the effort to handle) time-sensitive security incidents and customer escalations Estimate task complexity, communicate delivery timelines, and manage risks for projects executed by the team Ensure the team is running smoothly by eliminating technical barriers, coordinating cross-team dependencies, and focusing on the overall health and happiness of the team Contribute to planning for organizational growth, including allocation of engineering resources, future hiring plans, and assignment of projects Success Measures In the first month: Understand the high-level architecture of the Atlas Network Protection layer, the team's current projects, and the required day-to-day processes. Begin developing relationships with key stakeholders across Server, Atlas, and Product Security In three months: Take over full management of the team and begin building trust with your reports. Assume responsibility for day-to-day team operations. Be involved in reviewing designs for new features and helping the team navigate technical challenges. Hire engineers for the team as needed In six months: Establish yourself as a leader in the organization such that team members naturally come to you for guidance. Take over full ownership of Ingress Security’s software components. Lead the planning and execution of major features supporting the team’s major annual goals In twelve months: Perform a full annual cycle of performance and growth conversations with your team members. Contribute to the long-term vision for the Ingress Security stack and develop a plan to achieve that vision. Increase the capability and velocity of the team in measurable ways 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: 1273383870

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