WHO IS SONAR?

Sonar helps prevent code quality and code security issues from reaching production, amplifies developers’ productivity in concert with AI assistants, and improves the developer experience with streamlined workflows. Sonar analyzes all code, regardless of who writes it — your internal team, genAI, or third parties — resulting in more secure, reliable, and maintainable applications. Rooted in the open source community, Sonar’s solutions support over 30 programming languages, frameworks, and infrastructure technologies. Today, Sonar is used by +7M developers and 400K organizations worldwide, including the DoD, Microsoft, NASA, MasterCard, Siemens, and T-Mobile.
We believe in developing great products that are supported by great internal teams and a strong culture. We are highly committed to and obsessed with the company, users, each other, and our open source community. We have high standards and hold each other accountable for acting with positivity, dedication, thoughtfulness, empathy, and passion daily.
We are deliberate with our decisions with high clarity of intention. At the same time, we feel extreme urgency and move forward quickly.
And lastly, we are highly effective and operationally efficient. We operate collectively as One Team to accomplish our goals.
At Sonar, CODE is more than just an acronym – it’s a mindset that defines daily operations.

THE IMPACT YOU WILL HAVE:

The Sonar Code Next team is looking for a passionate Python Developer to join a fast-paced, dynamic group at the intersection of Large Language Models (LLMs), static analysis, and programming languages. Working on cutting-edge, AI-driven projects, you’ll help push the boundaries of automated code quality and security.
Our mission is to harness our expertise in static analysis and large language models (LLMs) to advance AI’s ability to understand, generate, and improve code. We develop prototypes grounded in cutting-edge research, testing innovations across the LLM development lifecycle—from data processing and model training to benchmarking. Our approach leverages techniques such as supervised fine-tuning (SFT), direct preference optimization (DPO), reinforcement learning from human feedback (RLHF), and retrieval-augmented generation (RAG) to enhance model performance and code quality.
As a key member of this team, you’ll directly influence AI-driven solutions by developing and refining the tools that make these initiatives possible. In this hands-on role, you’ll focus on implementing and optimizing methodologies that enhance code quality—ensuring that all solutions are scalable, maintainable, and ready for production.

THE EXPERIENCE YOU WILL NEED:

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• Proven expertise in Python development, writing clean, maintainable, and efficient code.

• Solid software engineering foundation, including algorithms, testing, CI/CD, and best practices for building scalable and reliable software.
• Deep curiosity about LLMs, static analysis, and multiple programming languages, recognizing their strengths, challenges, and nuances.
• Genuine interest in AI-driven software development, and a willingness to work on projects integrating AI with developer tools.
• Pragmatic approach to problem-solving, balancing research-driven innovation with building production-ready systems.
• Self-driven mindset, bold enough to challenge the status quo, yet humble and open to learning and feedback.
• Bonus points for hands-on experience with LLM-related projects, static analysis, or proficiency in additional programming languages (e.g., TypeScript, Java, C#).
• Initiative and Ownership: You can take a task from concept to completion with minimal supervision.
• Curiosity and Adaptability: You thrive in a fast-moving environment, staying eager to learn new technologies and experiment with AI-driven solutions.
• Open-mindedness and a Positive Attitude: You welcome new ideas, embrace feedback, and collaborate effectively with diverse teams.
• Comfort with Complexity and Change: You excel at navigating uncertainty, iterating quickly, and adjusting to evolving challenges.
• Confidence to Challenge and Be Challenged: You’re unafraid to question assumptions and engage in constructive discussions to drive the best outcomes.

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• Develop and maintain Python-based tooling and infrastructure to support AI-driven solutions for code quality and security.

• Implement and optimize AI-focused experiments, creating robust systems to evaluate modern techniques, including fine-tuning, retrieval-augmented generation (RAG), direct preference optimization (DPO), and reinforcement learning from human feedback (RLHF).
• Write scalable, production-quality Python code to support AI workflows, dataset processing, and evaluation frameworks.
• Design and maintain benchmarking pipelines to assess Large Language Model (LLM) performance in generating clean, maintainable code.
• Process and refine datasets, ensuring they’re structured and optimized for training and evaluation.
• Develop integrations between AI systems and static analysis tools, enabling AI-assisted insights for developers.
• Collaborate with static analysis experts and AI researchers to turn experimental ideas into practical, working solutions.
• Ensure the scalability, reliability, and maintainability of AI tooling as it transitions from experimentation to production.
• Continuously improve the development processes via workflow refinement, automation, and tooling for AI-assisted coding.
• Work in a fast-paced, iterative environment that bridges research-driven innovation with real-world software development.