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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

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

We are seeking a Senior Site Reliability Engineer to join our growing Gurugram Products & Technology team to provide technical direction, shape architecture, and build key operational foundations of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Senior Site Reliability Engineer on this new team, you will be responsible for enabling deployment at scale of AI applications and improving the performance, scalability, and reliability of the distributed systems infrastructure for this new product. The platform's SRE team owns the operational foundations: the Kubernetes fleet, networking, observability and alerting, and tenant isolation. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day – we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Position Expectations Operate and improve the multi-tenant Kubernetes infrastructure that runs customer workloads Build for reliability, making services and infrastructure available, resilient, fault-tolerant, and self-healing Identify and configure key metrics to detect incidents and quantify service health, availability, and performance Participate in a 24/7 on-call rotation to resolve issues involving platform infrastructure Mentor early-career SREs and contribute to the team’s operational practices as it grows Qualifications Strong background in software development and operating distributed systems 6+ years of experience building and operating distributed systems, with proficiency in Python, Go, or a similar programming language Experience operating Kubernetes in production and debugging below the abstraction layer, including scheduling, cluster networking, and node-level issues Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure Strong understanding of Linux operating system internals and networking concepts such as TCP/IP, DNS, TLS, and routing Customer-focused mindset and strong verbal and written technical communication skills, with a desire to collaborate with colleagues Strong bias for efficient processes, operational simplicity, and automation over manual work Bonus points for experience with Kubernetes networking, such as Istio or Cilium, service mesh or edge load balancing in production, secure multi-tenant runtime environments at scale, multi-cloud infrastructure management, and virtualization or workload isolation technologies Eager to learn, with a strong technical background 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 - 2273489536

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

The Team Platform Engineering sits within SRE and builds the core infrastructure powering MongoDB’s broader engineering organization. Our teams own everything from our multi-cloud Kubernetes foundation to automated deployment pipelines and global observability platforms. Within Platform Engineering, the Fabric team manages the global network substrate that enables secure communication between internal microservices and incoming public internet traffic. We own network architecture, service mesh topologies, and edge load balancing, ensuring customer data remains safe in transit. Ultimately, Fabric plays a pivotal role in engineering the reliable, globally connected, multi-cloud network that underpins all MongoDB products. This role is based remotely in the United States. Role Overview We are seeking a talented Senior Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As a Senior SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Be a US Citizen, as the position supports our FedRAMP authorized environment Have 5+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Be intimately familiar with modern cloud-based infrastructure and the network design primitives of at least one of AWS, Azure, or GCP, e.g. VPCs, subnetting, routing, VPNs, peering, private link / private service connect, and CDNs Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”) Have a strong knowledge of service mesh and load-balancing concepts, and be eager to implement these in a multi-cloud environment Expectations Contribute to a significant re-architecture of our multi-cloud globally-connected network, bringing your experience to design discussions and owning meaningful parts of the work Collaborate with service-owning teams to provide internal support, addressing technical issues and offering guidance on best practices for service-to-service connectivity Participate in a 24/7 on-call rotation to swiftly resolve issues related to network architecture and service-to-service connectivity, ensuring minimal disruption and high availability 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: 426185 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: $127,000 — $249,000 USD

MongoDB powers mission‑critical workloads for customers who expect their data to be durable, highly available, and fast to access. The Storage Execution team builds the core infrastructure that makes those guarantees real. We are hiring a Senior Engineering Manager to manage the largely New York-based Storage Execution team. This is a hands-on leadership role for someone who is obsessed with customer success, takes the responsibility of durably storing customer data seriously, and has strong empathy for both their team and our users. This role can be based remotely in the United States. About the Storage Execution team The Storage Execution team sits at the heart of MongoDB’s Online Transaction Processing (OLTP) team. We own the core transactional read/write path on each node, across both today’s storage engine and a next‑generation cloud-native storage architecture. Our work determines how correct and performant MongoDB is for customers running mission-critical production workloads. The team’s responsibilities include: Defining and maintaining the internal collection and index APIs used by Replication, Query and Catalog modules, and commands for local reads and writes, plus the transaction and durability primitives that govern visibility, conflict resolution and crash recovery Integrating the next generation of MongoDB’s storage architecture into the server in a way that is predictable for other teams, scales with cloud elasticity, and preserves the performance and safety of the classic configuration Improving transaction processing speed and semantics of both single shard and cross-shard transactions Owning index builds and schema‑level storage operations (build/rebuild, cleanup, resumability) and ensuring they behave well for large, highly available clusters running write-heavy workloads Building validation, diagnostics, and storage‑focused test infrastructure to catch durability issues early and keep the system trustworthy at scale Partnering with neighboring teams on flow control, prioritization and load-shedding to stay within resource limits, protecting durability and availability at the cluster level without starving critical operations What you’ll do Lead, grow and manage a New York–based team of 8 to 10 engineers; ensure clear expectations, high standards, and healthy, sustainable execution Own the team’s roadmap across durability, availability, performance, and developer productivity, in partnership with OLTP leadership and Product Management Manage customer escalations involving storage behavior and durability; work directly with Support, Atlas, and other server teams to reproduce, root‑cause, and resolve issues Drive process and tooling improvements that raise engineering velocity and code quality (e.g., ownership, review expectations, customer escalation and build failure practices) Partner closely with Replication, Query, Sharding, Catalog & Routing, Storage Engines, and Atlas teams on cross‑team features such as the new storage architecture, availability improvements, and workload management Represent Storage Execution in planning, staffing, and calibration; make thoughtful tradeoffs between near‑term deliverables, longer‑term availability gaps, and platform investments Candidate profile 8+ years building, debugging, and tuning distributed and/or highly concurrent systems software (databases, storage engines, filesystems, or similar) 2+ years managing engineers directly, including hiring, performance management, and coaching across a range of levels Willing to work East Coast hours Strong proficiency in at least one compiled, statically-typed language such as C++, Rust, or Go; prior C++ and systems programming experience is a plus Deep understanding of durability, availability, and performance tradeoffs in distributed systems; experience with replication, consensus, storage engines, or transactional systems is highly desirable Demonstrated customer obsession: direct experience working with demanding customers (or customer support / cloud teams) on complex incidents and turning them into clear, outcome‑oriented recommendations Proven ability to develop people: mentoring and promoting engineers, managing underperformance directly, and building high‑engagement teams with low regretted attrition Comfortable leading multi‑quarter initiatives with multiple stakeholders and using written documents to align teams on design, scope, and tradeoffs Success measures In three months, you have: Built strong relationships with your team and key partner teams Taken over team ceremonies, short‑term planning, and on‑call responsibilities Co‑led at least one active project and shipped one concrete process improvement In six to twelve months, you have: Led at least one cross‑team initiative in availability, durability, or developer velocity Delivered a multi‑quarter project with clear impact on durability/availability or team throughput Built a bench of engineers ready for increased scope and, over time, leadership roles 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, 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: 3273532708 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: $151,000 — $297,000 USD

MongoDB powers mission‑critical workloads for customers who expect their data to be durable, highly available, and fast to access. The Storage Execution team builds the core infrastructure that makes those guarantees real. We are hiring a Senior Engineering Manager to manage the largely New York-based Storage Execution team. This is a hands-on leadership role for someone who is obsessed with customer success, takes the responsibility of durably storing customer data seriously, and has strong empathy for both their team and our users. This role can be based remotely in Ontario, Canada. About the Storage Execution team The Storage Execution team sits at the heart of MongoDB’s Online Transaction Processing (OLTP) team. We own the core transactional read/write path on each node, across both today’s storage engine and a next‑generation cloud-native storage architecture. Our work determines how correct and performant MongoDB is for customers running mission-critical production workloads. The team’s responsibilities include: Defining and maintaining the internal collection and index APIs used by Replication, Query and Catalog modules, and commands for local reads and writes, plus the transaction and durability primitives that govern visibility, conflict resolution and crash recovery Integrating the next generation of MongoDB’s storage architecture into the server in a way that is predictable for other teams, scales with cloud elasticity, and preserves the performance and safety of the classic configuration Improving transaction processing speed and semantics of both single shard and cross-shard transactions Owning index builds and schema‑level storage operations (build/rebuild, cleanup, resumability) and ensuring they behave well for large, highly available clusters running write-heavy workloads Building validation, diagnostics, and storage‑focused test infrastructure to catch durability issues early and keep the system trustworthy at scale Partnering with neighboring teams on flow control, prioritization and load-shedding to stay within resource limits, protecting durability and availability at the cluster level without starving critical operations What you’ll do Lead, grow and manage a New York–based team of 8 to 10 engineers; ensure clear expectations, high standards, and healthy, sustainable execution Own the team’s roadmap across durability, availability, performance, and developer productivity, in partnership with OLTP leadership and Product Management Manage customer escalations involving storage behavior and durability; work directly with Support, Atlas, and other server teams to reproduce, root‑cause, and resolve issues Drive process and tooling improvements that raise engineering velocity and code quality (e.g., ownership, review expectations, customer escalation and build failure practices) Partner closely with Replication, Query, Sharding, Catalog & Routing, Storage Engines, and Atlas teams on cross‑team features such as the new storage architecture, availability improvements, and workload management Represent Storage Execution in planning, staffing, and calibration; make thoughtful tradeoffs between near‑term deliverables, longer‑term availability gaps, and platform investments Candidate profile 8+ years building, debugging, and tuning distributed and/or highly concurrent systems software (databases, storage engines, filesystems, or similar) 2+ years managing engineers directly, including hiring, performance management, and coaching across a range of levels Willing to work East Coast hours Strong proficiency in at least one compiled, statically-typed language such as C++, Rust, or Go; prior C++ and systems programming experience is a plus Deep understanding of durability, availability, and performance tradeoffs in distributed systems; experience with replication, consensus, storage engines, or transactional systems is highly desirable Demonstrated customer obsession: direct experience working with demanding customers (or customer support / cloud teams) on complex incidents and turning them into clear, outcome‑oriented recommendations Proven ability to develop people: mentoring and promoting engineers, managing underperformance directly, and building high‑engagement teams with low regretted attrition Comfortable leading multi‑quarter initiatives with multiple stakeholders and using written documents to align teams on design, scope, and tradeoffs Success measures In three months, you have: Built strong relationships with your team and key partner teams Taken over team ceremonies, short‑term planning, and on‑call responsibilities Co‑led at least one active project and shipped one concrete process improvement In six to twelve months, you have: Led at least one cross‑team initiative in availability, durability, or developer velocity Delivered a multi‑quarter project with clear impact on durability/availability or team throughput Built a bench of engineers ready for increased scope and, over time, leadership roles 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: 3273532708 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: $191,000 — $265,000 CAD