Sonar is driving the future of agent-centric software development. As the leader in AI code review and verification, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable.
Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code.
We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, Mastercard, NASA, Deutsche Bank, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like:
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SonarQube: The world’s leading AI code review and verification platform.
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SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.
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SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective.
Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE:
With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you.
The Impact You Will Have:
You will be the main technical architect responsible for how our most strategic enterprise clients and partners implement and deploy our machine learning solutions. As one of our first group of Forward Deployed ML Engineers, you will establish our ML solutions for organizations concerned with the quality, security, performance, and cost of coding models. You will leverage your deep ML expertise and technical skills to ensure successful, production-grade implementations, ultimately driving rapid market adoption through proven on-site technical success and client satisfaction.
End-to-End Ownership: Proactively engage with client or partner teams in Research, Engineering, Data Science, MLOps, Infrastructure to understand their business and technical requirements. With our internal R&D team in the loop, design specific implementations that you will integrate, optimize, and productionize within the client’s existing or greenfield systems as well as transferring technical knowledge to client teams when applicable.
Subject Expert: Stay up-to-date with the latest LLM capabilities and implementation patterns, you are learning driven. You will need to explain complex technical details and concepts to both technical and non-technical audiences.
Influence Model Training & Tuning: Represent our core R&D team on-site, leading technical engagement with modern techniques covering all stages of model training using complex, proprietary client data. Ensure architecture is aligned with and optimized for specific constraints (e.g. GPU types, air-gapping).
Develop Deployment Strategy: Define and execute a global technical strategy for integrating our ML solutions into diverse client environments, ensuring compliance with sector-specific data security standards and performance SLAs. Based on your implementations, build reusable playbooks and libraries that will accelerate yourself and others.
Building Relationships: Operate autonomously and with agency to build strong relationships with clients, create strategic technical partnerships and drive high-value, referenceable production deployments.
Serve as Internal Expert: Act as the primary internal consultant, advising product, research, and sales on real-world client infrastructure limitations, performance bottlenecks, and emerging technical standards necessary for product success.
Education: Bachelor's degree in Computer Science or a related field.
Experience: 2+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software/ML Engineer with consulting experience.
ML Engineering & Training Expertise: Experience in the Machine Learning lifecycle (training, optimization, deployment), with a proven ability to lead and execute complex model deployments in production environments.
Forward Deployed/Consulting Background: Proven track record working within or closely alongside client engineering teams to successfully deploy and integrate complex, high-performance software, involving cloud or on-premise ML workloads.
Technical & MLOps Knowledge: Understanding of modern ML frameworks, programming languages including Python, and deployment technologies (Docker, Kubernetes, cloud services like SageMaker/Vertex AI/Azure AI).
Value-Driven Influence: Demonstrated ability to influence senior technical leaders and lead engineers, translating complex model performance and system architectures into clear, tangible business value and deployment assurance.
Our culture and mission set us apart. We have a dynamic work culture that values respect and kindness and embraces the right to fail (and get right back up again!).
Great people make a great company. We value people skills as much as technical skills and strive to keep things friendly while still being passionate leaders in our domains.
We have a flexible work policy that includes 3 days in-office and 2 days work-from-home each week for those located near our office locations; some locations such as Dubai, India, Japan and Australia operate fully remotely.
We have a growth mindset. We love learning and believe continuous education is critical to our success. In an ever-changing industry, new skills are necessary, and we're happy to help our team acquire them.
As the leader in our field, our products and services are as strong as our internal team members.
We embrace transparency with regular meetings, cascading messages and updates on the growth and success of our organization.
We encourage usage of our robust time-off allocations with 27 PTO days for our employees based out of the Geneva region, plus additional days based on seniority and circumstances.
We contribute 60% of the total cost for your pension; 13.5% to 15.5% of your base salary for savings; 2% for risk.
Commuting:Sustainable mobility options, including carpooling and the refund of 60% of the annual transportation subscription.
Global workforce with employees in 20+ countries representing 35+ unique nationalities.
We have an annual kick-off somewhere in the world where we meet to build relationships and goals for the company.
