Job Description
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 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.
This role will be based out of North America.
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)
Good understanding of algorithms, data structures and their time and space complexity
Curiosity, a positive attitude, and a drive to continue learning
Excellent verbal and written communication skills
Nice to Have
Familiarity with cloud-native distributed systems (e.g., Kubernetes)
Experience with NoSQL databases and understanding of their trade-offs is great, but not required. We'll teach you NoSQL.
Contributions to relevant open-source projects.
Position Expectations
Contribute high-quality, well-tested backend code to the data migration engine and core components of our generative AI orchestration platform
Collaborate effectively with Product Management, AI researchers and machine learning engineers and designers to build and deliver on the product roadmap
Work to develop robust and efficient backend services that orchestrate AI functionalities
Identify and address performance bottlenecks and architectural challenges in our systems, particularly within data flow and orchestration
Participate actively in code reviews to enforce best practices and patterns
Help troubleshoot and resolve complex technical issues in our distributed systems
Give and solicit feedback on technical design documents and pull requests
Perform tasks related to process such as CI/CD, quality, testing, etc
Success Measures
Within the first three months, you will have:
Familiarize yourself with the MongoDB database and aggregation language
Familiarize yourself with the backend tech stack including Java, Spring Boot, and Kafka
Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks
Started collaborating with your peers and contributed to code reviews
Within six months, you will have:
Familiarised yourself with the rest of our the application modernization tool stack
Delivered at least one large scale feature that spans the entire tech stack
Reviewed and contributed to scope and technical design documents
Within 12 months, you will have:
Become a key contributor to our backend stack, capable of taking on complex features independently
Helped recruit and interview new members of the team
Collaborated effectively with other teams at MongoDB on cross-functional projects
About MongoDB
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database 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 database and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and nearly 60,000 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.
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.
MongoDB’s base salary range for this role in Canada is:
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