About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks tha…
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 syntax tree (AST)
Provide thought leadership to the engineering team on using emerging technologies, frameworks and approaches to solve different problems
Collaborate closely with product managers and other engineers to understand business priorities and propose new solutions
Contribute and maintain the high quality of the codebase with tests that provide a high level of functional coverage and non-functional aspects with load testing, unit testing, integration testing, etc
Share your knowledge by giving brown bags, tech talks, and evangelising appropriate tech and engineering best practices
Define and improve business & product metrics to optimise the quality and cost of AI usage
Success Measures
Familiarise yourself with the MongoDB database and aggregation language
Familiarise yourself with the problem space and the domain
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
Worked on and delivered a large-scale AI-based feature in the product
Contributed to and helped deliver a few releases of the product
Reviewed and contributed to scope and technical design documents
Delivered large-scale features across our entire tech stack
Helped recruit and interview new members of the team
Collaborated with other teams at MongoDB
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-nativ
Neutral 2–4 sentence summary of what working at this company is like, drawn from public reviews and press coverage. Tone, collaboration style, pace, benefits highlights.
£45,000 – £60,000 (Glassdoor, Levels.fyi, 2025)
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