Senior Software Engineer, Application Migration at MongoDB – Sydney | Jobyssey

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 software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

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 is an equal opportunities employer.

Requisition ID1273418213

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The ideal candidate for this role will have

Nice to Have

Position Expectations

Success Measures

About MongoDB