Senior Software Engineer, Application Migration

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 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 data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of

6+ years of engineering experience in backend systems, distributed systems, or core platform development. Proficiency in Java, Rust, C/C++, and/or Python with 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 written communication skills.

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. 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.