Engineer Ip Verification Jobs

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. 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, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. 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, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

The Storage Layer Services team is currently re-architecting the MongoDB Cloud Storage Layer. This is a relatively new team in MongoDB that sits at the heart of the next generation MongoDB Cloud Storage Architecture, and the team is working to build performant multi-tenant distributed storage services both to enhance our existing MongoDB cloud storage architecture and to power more of our customers' use cases more efficiently. Engineering at MongoDB is globally distributed, with a mix of folks being fully remote, hybrid, or in-office. We have a small but growing team that calls Sydney home, and we are looking for a Staff Engineer to join the team working closely with other teams in Sydney and North America. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to work on a collaborative team that applies great engineering fundamentals to deliver core features of a popular database, join us! Let’s change what’s possible for application developers, system architects, and database operators. We are looking to speak to candidates who are based in Sydney for our hybrid working model. You’re an ideal candidate if: You have 10+ years of experience in programming, debugging, and performance tuning highly concurrent and/or distributed systems. Especially if you have worked in a systems language (C, C++, Rust, etc) for a number of those years You have a track record as an effective technical leader. You love helping teams be successful at solving vaguely defined problems in iterative and measurable ways. You put the customer first, and don’t hesitate to cross team boundaries in search of the right solution You have a solid grasp of related systems fundamentals, such as cache management, log-based recovery, transactions or performance profiling You’re comfortable reasoning about highly concurrent, asynchronous services — backpressure, tail latency, and the failure modes of replicated state machines You’ve worked on large, highly availabl

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 seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. This is an opportunity to join a team that is responsible for all Observability systems that support metrics, metric visualization, logs, traces, and alerts for MongoDB. We are looking for engineers with high standards, and experience in setting direction and technical leadership for large engineering teams in designing and operating complex distributed systems, with strict SLO on security, durability, availability and performance. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Splunk, Flink, WarpStream/Kafka, Java, Golang Fluentbit. In addition to owning critical components of our observability infrastructure, as a Staff engineer on the team, you’ll also work closely with other SWE, Product and SRE teams to promote and implement best practices in instrumenting and monitoring their services. This is a highly collaborative role, and you will get to own some of the most relied upon internal infrastructure at Mongo. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies low-level systems expertise to build the foundational infrastructure of a popular database, join us! Let’s build a faster, more reliable, and exceptionally observable database system together. W

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

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

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 bolstering its hiring, focusing on creating tools that guide customers in transitioning their applications from relational databases to MongoDB. As businesses evolve their application development frameworks, they're increasingly drawn to the versatility of the document model. The Relational Migrator team, already instrumental in this area, aids developers in making the shift from relational databases to MongoDB. Now, they're broadening their toolkit and are keen on refining code using a mix of AI and traditional text processing. MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to helping users navigate code conversion challenges with AI's support. This role will be based out of North America in the PST and MST zones only. The ideal candidate for this role will have 2+ years of professional software development experience in Java or another programming language Experience with generative AI and specifically LLMs is highly desirable Experience with text processing engines such as ANTLR is highly desirable Strong understanding of software engineering, system design, data engineering and/or cloud architecture Have experience with compiler design, code parsing or related areas Familiarity with concepts like abstract syntax trees (AST), lexical analysis, and syntax analysis Curiosity, a positive attitude, and a drive to continue learning Actively engages in emerging trends and research relevant to product features Excellent verbal and written communication skills Position Expectations Collaborate with stakeholders to define and implement a code modernisation strategy, ensuring that transformed code aligns with modern software practices while preserving original functionality Develop and maintain a robust code parser to accurately interpret legacy code structures, converting them into a standardised format like an abstract

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

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. 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 builds and maintains the instances and supporting infrastructure powering Atlas Search. This platform deploys and monitors search deployments, providing a highly scalable yet observable system for customers and engineers. The Atlas Search product is quickly gaining traction with customers and we are shipping core infrastructure components that enable this growth. This role is based in San Francisco, CA with an in-office or hybrid work model. Successful candidates will have the following qualities: 2+ years of hands-on experience designing, building, testing, and maintaining industrial-strength backend software and automation in complex codebases Experience developing distributed systems and multithreaded applications Familiarity with public cloud platforms, distributed infrastructure, and metric-based development Experience with at least one modern statically typed program

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.

This new team will architect the platform foundation and infrastructure that enables a "build once, run anywhere" model, ensuring our AI-powered modernisation suite operates seamlessly regardless of a client's security or network constraints. We are looking for engineers to join this high-visibility initiative, where you will solve unique distributed systems puzzles and help shape the future of how global enterprises leverage GenAI. We are looking for an experienced software engineer who thrives on solving infrastructure constraints and building enterprise facing platforms. The ideal candidate is a hands-on technical leader who can architect complex distributed systems, mentor engineers, and collaborate with product teams to deliver a platform that minimizes deployment friction and meets customers’ compliance requirements. This role can be based out of our Gurgaon office or Remotely in India. The ideal candidate for this role will have 8+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure 2+ years of experience leading, coaching, and mentoring a team of engineers to achieve high-impact results Deep experience designing distributable applications that run in air-gapped or highly restricted network environments Strong proficiency in containerization and orchestration, with the ability to design systems where the host executes containerized applications under strict security monitoring Experience building Service Host architectures that provide shared routing, proxy layers, and API gateways for multiple underlying services Experience managing persistent storage solutions (blob/file storage) within distributed systems Understanding of security-first design, specifically regarding the execution of untrusted code, fine-grain access control, and rigorous input validation Experience designing auto-update mechanisms for software that cannot directly access the public internet Curiosity,

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