Codex Deployment Engineer Jobs

Come join 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 talented Staff Engineers 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. If you want to be a key technical leader on a collaborative 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 10+ years of experience building production-quality systems software with a large user base, robust design structure, and rigorous code quality Experience with large backend/compiled codebases and performance-sensitive software, preferably in Rust Bonus points for experience working hands-on in security-sensitive or networking-adjacent domains Strong systems fundamentals, including multi-threaded programming and performance profiling. Bonus points for: Understanding of network protocols, TLS, and connection lifecycle management. Familiarity with security concepts such as attack surface reduction, input validation, memory safety, and defense-in-depth architectures. Excellent verbal and written technical communication skills for communicating to a wide variety of audiences ranging from junior engineers to executive stakeholder Strong mentorship skills, and excitement about leveling up your peers and teammates through coaching, feedback, and enablement Strong time management skills and the ability to realistically assess project complexity B.Sc. in Computer Science or a related

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

Join the MongoDB Server Query team, and help us build a world-class distributed open source query engine. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, from parsing to optimization to plan selection and finally execution. This also includes our geospatial search and update subsystems. Our global team is growing fast. In North America, we have a presence across the US and Canada including New York, West Coast, Toronto. In Europe, we have a presence in Dublin, Germany, France, Netherlands, UK, Bulgaria, Spain and Italy currently. We support office-based and remote work and align projects with convenient work hours for each time-zone. We have tons of interesting problems to solve with direct impact on users for transactional, time-series and analytical workloads. We need your help to design and build the heart of a distributed, flexible schema, document database. 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 in data intensive environments Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases B.Sc in Computer Science or similar field, or equivalent practical experience Experience in C++ and in developing database systems is a plus Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Position Expectations Understand and improve current functionality of the MongoDB query engine Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work with other engineers to

Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. This role is based in Toronto, ON hybrid. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and cloud services Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a solid high-level understanding of what our team does and how we operate.

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

We are looking for a Technical Director to join Builder Relations, leading our team of talented Advocates in APAC. As more developers choose MongoDB as their data platform, your responsibilities will include directly engaging with customers and the community to deliver meaningful experiences and inspiring content. You will empower developers—from startups to Fortune 500 companies—to integrate advanced data and AI capabilities into their applications and solutions. If you are passionate about equipping builders and cultivating a vibrant developer ecosystem, we invite you to join us in shaping the future of development on MongoDB. Our Builder Relations teams are distributed across the globe, with most members working remotely. To see what our team is doing, check out our content on YouTube , Dev , and Medium . This role can be remotely in the India region. Candidate Profile We are excited to welcome a technical leader to our team who, as a player & coach, will drive engagement with customers and the community in India and across the region. At the foundation of your expertise is a love to equip others through hands-on workshops, architectural reviews, and building relationships directly with customers, and at events and user groups. To be successful, you will have at least 10 years of experience as a database expert, and 5 years of experience as a people manager. Ideally, you will have additional experience in a customer-facing role (such as solution architect), teaching, or related technical role, where you’ve led or advised teams as they solve their enterprise's most critical data challenges, and have distributed code and content to support others. You are known for your deep database expertise (familiarity with other data technologies and the ability to quickly become proficient in MongoDB), your insight into developer enablement programs, and your ability to guide development teams in the adoption of new technologies. You’re an excellent public speaker a

Atlas Search is a multi-cloud service that allows users to execute complex full text and vector search queries using the MongoDB Query Language . Our users are free to focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building the cloud-based distributed systems software responsible for the lifecycle of search indexes including: data ingestion, index building, partitioning, performance, availability, and backup management. Our product is quickly gaining traction with customers and we are making core architectural improvements that you will contribute to. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software in a complex codebase Experience developing distributed systems and multithreaded applications Experience with at least one modern statically typed programming language, and interest in working with Java Excellent verbal and written technical communication skills and enthusiasm for collaborating closely with colleagues A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback A strong sense of ownership over their work, from initial design all the way through maintaining code in production You will: Contribute to the design, implementation, and support of projects that improve the scalability of Atlas Search to make using it a seamless experience for even the largest workloads Work with a collaborative team that prioritizes sound technical decision-making and building systems that our customers love and that we are proud of as engineers Have the opportunity to lead projects and own subsystems Provide input on the team’s roadmap and help determine the architecture of our system Success measures: In 3 months you’ll have a

Staff Forward Deployed Engineers (FDE) sit at the intersection of enterprise customer environments and a fast-moving internal product. They are senior technical leaders who own ambiguous, high-impact problems that span customer engagements, product direction, and engineering execution. They are accountable not only for getting customers to production, but for using what is learned in the field to shape reusable product capabilities, technical strategy, and delivery quality across multiple teams. This role is best suited for engineers who want to combine hands-on technical depth with broad influence: defining or changing strategy when customer reality reveals a gap, guiding technical decisions across teams, and translating field insight into durable product and engineering improvements. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities Customer and business impact Own the most complex customer engagements and technical workstreams, especially where the problem, solution, or path to production is ambiguous Build deep understanding of customer architecture, business goals, constraints, and definition of success, and use that understanding to shape the technical approach rather than only execute within a predefined one Act as a trusted technical counterpart to customer’s engineering leaders, internal product and engineering leaders, and executive stakeholders when navigating complex tradeoffs, risks, and priorities Technical leadership and execution Lead architectural design for customer-facing solutions and platform capabilities within the FDE domain, balancing hands-on implementation with technical decision-making across multiple teams Take ambiguous, high-level problems and turn them into clear technical direction, implementation plans, milestones, and ownership boundaries that enable execution at quality and speed Continue to write and review production-quality code, troubleshoot complex failures, and set

Atlas Growth is a cloud engineering group whose mission is to guide customers through their app development journey—from cluster configuration, data modeling and load testing, to running a production workload at scale. We use an in-house experiments platform which helps us validate our features quickly, releasing only the work that positively impacts our customers. Our engineers participate in cross-functional “squads” with product, design, analytics, and research focusing on a single metric (e.g. retention). Our engineering team is part of a larger Atlas Core Engineering org, building foundational elements of MongoDB’s developer data platform. Atlas Growth 2 builds customer-facing features in Atlas and sits alongside other Growth engineering teams. Recent projects include an AI Chatbot for cluster creation, a recommendation system that offers tips for better database performance, and a pricing page designed to optimize conversion rates. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Role Overview Atlas Growth seeks a mid-level software engineer (Software Engineer 3). SE3s are solid contributors to projects they work on and often lead projects of their own. They act in accordance with MongoDB’s core values and leadership principles, and are actively working toward a Senior role. Candidate Profile 3+ years of software engineering experience, with fluency in TypeScript/JavaScript, and experience with a modern framework (e.g. React) Proficiency in Java, Go, C++/C, or a similar compiled language is a plus Experience writing database queries, either document-based or relational Experience writing and reviewing technical specs, and leading small projects Interest in A/B testing or product design Expectations Contribute readable and well-tested code to ongoing projects Collaborate closely with product and design partners to implement and iterate on new customer facing features Write scope and technical spec docs for new projects

Join the Atlas Search Query team to design and develop the next generation of Search query architecture, optimization, and execution. Atlas Search is a growing cloud service that allows users to execute complex search and vector search queries using the MongoDB Query Language. Our users can focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the success of complex Search Query feature development. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. What You’ll Do Lead complex projects across the MongoDB ecosystem, for instance, development of a new Search aggregation framework within the MongoDB aggregation framework. Set project level strategy, architect features, and lead projects to successful execution Identify, design, and implement features enhancing our query language, performance, and operability Perform code reviews with peers and make recommendations on how to improve our software development processes Influence and grow team members through active mentoring and leading by example What We Look For 5+ years experience in data management/search systems, ideally with a strong query processing and optimization background Experienced in the development and maintenance of stateful distributed systems Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others Experienced in debugging and profiling multithreaded applications written in Java and Rust Bonus: experience with designing high-volume query engines, such as a datab

The Atlas API Experience (APIx) teams are part of MongoDB Atlas Data Services, a diverse group of individuals who develop the capabilities to run MongoDB globally (see MongoDB Atlas ). Our software and services allow users to deploy fault-tolerant, scalable, globally distributed MongoDB clusters in minutes. APIx’s mission is to create delightful experiences that bring developers along on the journey from eager beginner to sophisticated MongoDB expert! As part of our team in APIx, you will be responsible for improving & extending our API platform & downstream tooling, such as the Atlas CLI . Our mission is to help Atlas customers automate their workloads easily through APIs & support internal teams contributing to the API. We are looking for passionate, intrinsically-motivated software engineers who lead by example, raise the bar for those around them, and want to make a broad impact. No prior experience with MongoDB technologies is required! During interviews, you will meet most of our team and have the opportunity to ask questions about working at MongoDB. We pride ourselves on our team's culture and on being an inclusive and collaborative group that Builds Together . This role can be based in our Dublin office or remotely within Ireland. What will you do? Propose, design, implement and support product features for the MongoDB Atlas API Platform & MongoDB Atlas DevTools, such as AtlasCLI Build tooling that enables MongoDB users and developers to succeed, using programming languages such as Java, Go, Python & Javascript/Typescript Design and develop software integration components utilizing MongoDB’s technology (i.e. database, mobile, search, etc.) in larger contexts and integrate into partner frameworks or solutions Mentor and provide technical guidance to other engineers through code and design reviews, pairing, and knowledge sharing Lead sophisticated projects end to end, breaking large efforts into incrementally shippable deliverables Investi

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