Codex Deployment Engineer Jobs

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale with trillions of data points per day, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams for tens of thousands of companies globally. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team The Datadog Security Libraries team owns the customer-side integrations behind our run-time security products App & API Protection , Workload Protection , and Code Security . Our libraries let customers automatically manage application security risk with continuous, real-time monitoring of vulnerabilities and threats against their web applications, serverless applications, and APIs, in production. Automatically integrated with Application Performance Monitoring (APM) distributed tracing and code-level context, our software empowers development, operations, and security teams to build and run secure applications. As a polyglot team we ship and maintain the security capabilities of Datadog's tracing libraries across .NET , Java , Go , Node.js , Python , Ruby , and PHP , on top of a shared C++ core and a set of HTTP proxy integrations (primarily Envoy, NGINX, and HAProxy). Our code runs inside thousands of production applications around the world. Recent work spans exploit prevention (RASP) and WAF detections, API Security, code security (IAST and SCA), and AI-assisted ("agentic") onboarding, always measured by real product outcomes and operational telemetry. The Opportunity We're looking for a senior, polyglot engineer to contribute across several of our security libraries, with .NET or Java expertise. You'll design and build security integrations and detection features, take them from prototype to production-hardened, and own them operationally as they instrument thousands of applications. As a se

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale with trillions of data points per day, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams for tens of thousands of companies globally. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team The Datadog Security Libraries team owns the customer-side integrations behind our run-time security products App & API Protection , Workload Protection , and Code Security . Our libraries let customers automatically manage application security risk with continuous, real-time monitoring of vulnerabilities and threats against their web applications, serverless applications, and APIs, in production. Automatically integrated with Application Performance Monitoring (APM) distributed tracing and code-level context, our software empowers development, operations, and security teams to build and run secure applications. As a polyglot team we ship and maintain the security capabilities of Datadog's tracing libraries across .NET , Java , Go , Node.js , Python , Ruby , and PHP , on top of a shared C++ core and a set of HTTP proxy integrations (primarily Envoy, NGINX, and HAProxy). Our code runs inside thousands of production applications around the world. Recent work spans exploit prevention (RASP) and WAF detections, API Security, code security (IAST and SCA), and AI-assisted ("agentic") onboarding, always measured by real product outcomes and operational telemetry. The Opportunity We're looking for a senior, polyglot engineer to contribute across several of our security libraries, with .NET or Java expertise. You'll design and build security integrations and detection features, take them from prototype to production-hardened, and own them operationally as they instrument thousands of applications. As a se

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

As a Staff Engineer on the Data Platform Experience team, you'll help shape how Datadog engineering teams build, operate, and evolve products on the Observability Data Platform. You'll lead the design and delivery of shared platform capabilities that reduce developer friction, improve operational visibility, and enable engineering teams to move faster with confidence. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in the code. You'll have the opportunity to solve company-wide challenges spanning cost intelligence, operational tooling, platform health, and developer experience. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead strategic engineering initiatives that improve how product teams build, operate, and evolve services on the Observability Data Platform. Design and build scalable platform capabilities for cost intelligence, including cloud cost allocation, trend analysis, and optimization recommendations. Develop operational intelligence and self-service tooling that helps engineering teams understand platform health, troubleshoot incidents, and improve operational efficiency. Drive reusable platform services and developer workflows that increase engineering autonomy while reducing operational complexity across multiple products. Provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on technical contributions. Participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence. Who You Are: You have experience designing and building large-scale SaaS or cloud platforms with deep expertise i

We’re looking for an Engineering Manager to lead our Sensitive Data Scanner (SDS) Telemetry team. The SDS group’s mission is to be the world’s easiest-to-use tool to discover, classify, manage, and report sensitive data risks across cloud, on-premise, and code environments. This team builds and scales the detection capabilities that scan all telemetry data flowing into Datadog — logs, APM spans, and RUM events — operating in streaming, at processing time, and at very large scale. You’ll lead a small, close-knit team based in Paris, with the opportunity to shape how the team grows as SDS Telemetry’s scope expands. It’s a chance to combine hands-on technical leadership with direct customer and product impact in the security and observability space. At Datadog, we place value in our office culture — the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and grow a team of engineers building real-time sensitive data detection across Datadog’s Logs, APM, and RUM telemetry pipelines Partner closely with the Logs, APM, and RUM teams, plus Datadog’s Trust & Safety team, to align on roadmap and integration priorities Shape product direction by working closely with Product, grounding decisions in customer needs and business impact Stay hands-on: contribute to design decisions and participate in the team’s on-call rotation Recruit, mentor, and develop engineers as the team grows beyond its initial size Help build a strong engineering culture as part of Datadog’s broader Sensitive Data Scanner group Who You Are: You have experience building and shipping revenue-generating products, with strong product acumen and a customer-first mindset You have hands-on experience with Go and/or Java, and a track record building distributed, streaming systems at scale You have experience managing engineers — or are

We are a team of engineers that translate our real-world experience to help our user communities solve problems. With a focus on AI-accelerated workflows and next-generation developer ecosystems, you will have the opportunity to meet fast-moving teams where they are, helping them lay strong engineering foundations and broadening your impact to the developer community at large. This is a unique opportunity to use both your engineering depth and authentic storytelling skills to shape how the next wave of builders approach software health, scalability, and observability. What You’ll Do: Help developers hone their craft in an AI-accelerated world by exploring how AI coding assistants and rapid-prototyping tools change software workflows, and guiding teams on how to balance rapid prototyping with established engineering practices around performance, code health, and system reliability. Build in public by creating authentic, peer-to-peer technical content, sharing your engineering insights directly where modern developers collaborate in person and online. Drive a constructive, bidirectional feedback loop between fast-moving developer communities and our internal teams, translating real-world developer experiences into actionable product insights to shape our roadmap while advocating for user needs from the inside. Design and ship high-quality open-source boilerplate templates, quickstarts, and tools that make integrating observability seamless across AI native workflows, next-gen platforms (Vercel, Supabase, etc.), and cloud providers (AWS, GCP, Azure). Who You Are: A builder with approximately 10+ years of software engineering experience, ideally having shipped applications from scratch or worked within an early-stage startup environment where you've worn multiple hats. An AI-fluent developer who natively leverages AI coding assistants and rapid-prototyping tools as a core part of your regular, day-to-day development workflow. Multi-stack familiar, comfortable writing an

Join the Vector Search team and help build a cutting-edge vector database on top of MongoDB. Our team is responsible for the syntax and implementation of MongoDB's $vectorSearch aggregation, which enables approximate nearest neighbor queries over high-dimensional vectors. We are a small team with a large and rapidly growing customer base, providing engineers an opportunity to make a highly-visible, broad impact. When scaling search to billions of vectors, performance is paramount. We're looking for engineers who enjoy solving complex and open-ended problems that directly impact users' performance. This role is based in San Francisco, CA with a hybrid work model. You would get to: Implement new features within MongoDB's $search and $vectorSearch aggregation operators Work cross-functionally with Product teams to define new query and index syntax Identify and address performance bottlenecks in filter queries and nearest neighbor search Have the opportunity to lead projects and own subsystems Perform code reviews with peers, review technical designs, and mentor junior developers Ideally you will be: 3+ years of experience working on large-scale backend systems Experience writing high-performance applications in Java or another JVM language A growth mindset and the desire to learn quickly through taking on challenges, reflecting on outcomes, and incorporating feedback Passionate about optimization, code quality, and problem solving Bonus: experienced with Apache Lucene, vector databases, or high-throughput web services Success Measures In 3 months you'll have a solid high-level understanding of what our team does and how we operate You'll have contributed to the development of an existing project and completed several small improvements or bug fixes In 6 months you'll be reviewing code and project designs, and be an active participant in team meetings In 12 months you'll have a thorough understanding of the systems our team owns and have led a small project. You'll have

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization. We're looking for a Software Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges. This role will be based out of Washington, Oregon, or California. The ideal candidate for this role will have 2+ years of engineering experience in backend systems, distributed systems, or core platform development Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory ma

The MongoDB Query Execution Team is hiring software engineers who want to join us in developing a high performing, reliable and modular distributed query system. Our engineers work on implementing and maintaining execution algorithms, building new query language features, tuning database performance, and more to power our customers' critical workloads. This role can be based out of our Dublin office or remotely in Ireland. Relocation can be supported. Position Expectations Understand and improve current functionality of the MongoDB query engine Contribute high quality C++ code and give and solicit feedback in code reviews 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 constructively with peers to deliver excellent technical solutions Candidate Profile 5+ years of experience in systems programming Experience in databases and/or data management systems is a huge plus, but not a requirement 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, preferably in C++, C, Rust or a similar compiled language B.Sc in Computer Science or similar field, or equivalent practical experience Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Success Measures In three months you’ll have contributed to the development of a project slated for the next major version, as well as fixed a few bugs in a minor version of our latest stable release series In six months, you’ll have taken on code review responsibilities and are independently delivering complex functionality and squashing bugs independently In twelve months, you’re leading the development of a new major feature and are h

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

We're looking for a Senior Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges.. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate for this role will have 6+ years of engineering experience in backend systems, distributed systems, or core platform development. Proficiency in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning. Extensive experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium Extensive experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) Exposure to client-side technologies such as JavaScript and React is a plus 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 wri

The Team Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, networking, load balancing (including our public-facing edge and internal service mesh), and observability and alerting systems. The Fleet Management team provides the core runtime environment that empowers our developers to build and ship products to delight our customers. We manage the end-to-end lifecycle of our Kubernetes fleet, alongside the critical components that ensure cluster reliability and security (e.g., CoreDNS, cert-manager, and Gatekeeper). As our infrastructure scales to support new use cases and products, we are spearheading a migration from Terraform-based Infrastructure as Code (IaC) to an Operator-driven lifecycle management model. This role can be based out of our Austin, Boston, Los Angeles, New York City, Raleigh, or San Francisco offices, remotely in the United States region, or our European office in Dublin. Responsibilities Contribute to developing and maintaining a scalable and secure runtime environment on top of Kubernetes that supports product needs across MongoDB Provide internal support for our Kubernetes ecosystem, partnering with engineering teams to help them solve domain-specific problems Participate in a 24/7 on-call rotation to resolve critical issues Prioritize blameless post-mortems and dedicate engineering time to systemic fixes, ensuring you aren’t paged for the same issue twice You may be a good fit if you Have 6+ years of experience in software development and operating distributed systems Are proficient in Go, Python, or a similar language, with a strong commitment to code quality and testing practices (writing unit, integration, and E2E tests) Have deep experience using and extending containerization technologies, preferably Kubernetes Have a solid understanding

MongoDB’s Replication Team builds the infrastructure that enables high availability, fault tolerance, automatic failover, and tunable consistency. As an engineer on the team, you will design and implement distributed-systems features that protect data and keep applications available under demanding operating conditions. You will work primarily in C++ on core database code, partner with engineers across MongoDB, and help shape features that are central to major MongoDB releases. This is an opportunity to apply distributed-systems fundamentals to a widely used database while solving challenging problems in correctness, performance, and operability. We're looking to speak with candidates based in New York City for our in-office working model. What you will do Design and implement replication features based on the Raft consensus protocol Improve failover behavior, availability, correctness, and performance across the replication system Write production-quality C++ and the unit, integration, and system tests needed to demonstrate correctness Use JavaScript and Python where appropriate to extend test coverage and validate end-to-end behavior Diagnose test failures, investigate bugs, and drive issues through root-cause analysis and resolution Measure the performance impact of code changes and prevent or resolve regressions Collaborate with partner engineering teams and stakeholders on large, cross-functional initiatives Investigate distributed-systems issues raised by customers and Technical Support, communicate findings clearly, and help deliver durable fixes Participate in code reviews, design reviews, and technical discussions that improve the quality of the team’s work Interview candidates and mentor junior engineers and interns What you bring Required At least five years of experience programming, debugging, and performance-tuning distributed or highly concurrent software systems Strong systems fundamentals, including multithreaded programming, concurrency, debugging,

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Senior Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate will have 5+ years of commercial software development experience with strong proficiency in Python and/or Java Extensive Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query opti

The Site Reliability Engineering team designs and builds the global infrastructure on which we deploy our services, focusing on the above mentioned flagship MongoDB Atlas platform. As our customers grow and globalize, our services must satisfy demands for low-latency requests around the globe, and comply with various data sovereignty requirements. The SRE Team’s mission is to build this increasingly complex infrastructure, while continually lowering the operational burden associated with it, and increasing our internal visibility into the health of the system. We are strong believers in infrastructure-as-code and self-healing systems. The SRE Team is fully integrated with all the other engineering teams, and the teams work closely together with a soft and traversable boundary between their areas of responsibility. We are looking to speak to candidates who are based in New York City for our hybrid working model. Responsibilities Design and build the infrastructure for a global cloud service that comprises hundreds of thousands of MongoDB clusters, processes a billion metrics per day, and replicates tens of billions of database writes to our backup service Design, implement, and troubleshoot the automation and monitoring of services that seamlessly spans the globe - including several cloud providers Become an expert in infrastructure performance, helping us optimize from the application level all the way through the firmware Build for resilience. Our goal is that nobody’s pager goes off, ever. Are we there yet? No. Are we really close? Very. While we work on that - participate in a weekly on-call rotation Improve our infrastructure capabilities, optimizing for cost, simplicity, and maintainability Requirements 3+ years of experience running a mission critical service at scale in a Linux environment Firm grasp of at least one modern programming language, beyond basic scripting Familiarity with web and network protocols and standards (HTTP, TLS, DNS, etc) Bachelor’s deg