Research Engineer

Position description

At Sonar, we are seeking an innovative Research Engineer to join our Data & Agentic team and pioneer the next generation of our code analysis and verification engines. You will be at the forefront of applying cutting-edge AI, advanced agentic workflow and static analysis techniques to complex source code. Your work will directly shape our core products-ensuring both AI-generated and developer-written code meets rigorous enterprise quality and security standards. If you are driven to turn state-of-the-art research into practical, high-impact solutions, this is the role for you.

What you will do

• Create & Innovate: Actively participate in the conceptualization phase. Brainstorm novel ways to improve our products and provide immediate, practical feedback to steer exploratory research toward paths that are both impactful and engineering-feasible.
• Develop Agentic Workflows: Design, prototype, and validate intelligent agentic systems and automated workflows that facilitate writing clean code, identifying root causes of system issues, and remediating complex bugs and vulnerabilities.
• Develop Pragmatic Prototypes: Build hands-on prototypes that prove the viability and scalability of research concepts. Proactively identify engineering bottlenecks or scalability limits and propose effective mitigations early in the research phase.
• Evaluate & Benchmark: Drive the rigorous evaluation of new product features. Construct high-quality datasets, define relevant success metrics, and implement comprehensive benchmarks leveraging Sonar’s existing IP alongside third-party and open-source AI tools.
• Engineer Data Pipelines: Build and manage robust data pipelines to gather, process, and version massive code-centric datasets required for training and evaluating specialized models at scale.
• Translate Prototypes to Products: Collaborate closely with engineering and product teams to integrate successful prototypes into Sonar's cutting-edge products, ensuring they meet the needs of our global user base.
• Communicate and Evangelize: Clearly articulate and document complex technical concepts and research findings to both technical and non-technical stakeholders.

Experience and qualifications

Must have:

• Advanced academic background in Computer Science, Machine Learning, or a related quantitative field.

• Strong software engineering experience (minimum 2+ years in industry) with proficiency in Python and major modern programming languages.

• Practical experience with modern agentic frameworks, software automation tools, and LLM architectures.

• Experience of driving research projects from initial ideation to a demonstrable prototype with a high degree of autonomy.

• Hands-on experience integrating third-party tools, program analysis frameworks, or open-source libraries into functional prototypes.

• Proven experience in data handling: constructing high-quality datasets, defining objective success metrics, and building robust benchmarks for new solutions.

• The ability to fast context-switch and maintain momentum across multiple concurrent, fast-moving research topics.

• Excellent communication skills in English, with a talent for translating complex research findings into clear, actionable artifacts for product engineering squads.

Plus:

• Background in static analysis: abstract syntax trees (ASTs), code security, bug detection, etc..

• Familiarity with LLM techniques such as model fine-tuning, semantic search engines, etc.

• Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS).