Staff AI Engineer

At Sonatus, we’re driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can’t keep pace with consumer expectations shaped by the mobile industry—where features evolve rapidly, update seamlessly, and improve continuously. That’s why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we’re solving some of the most interesting and complex challenges in the industry. Join us and help redefine what’s possible as we shape the future of mobility. Role Summary: Sonatus is seeking a highly motivated Staff AI Engineer to define and develop next-generation agentic AI applications for software-defined vehicles. You will be critical in accelerating software innovations that solve complex, real-world customer problems. Responsibilities: Lead the architecture and development of end-to-end software solutions leveraging agentic AI (e.g., LLMs, agent frameworks, RAG, context engineering, and evaluation). Design and implement robust data orchestration and processing pipelines for continuous agent operations and performance improvement. Translate complex customer problems and business requirements into effective, deployable AI solutions. Requirements: Proven experience in designing and deploying end-to-end agentic AI systems in a production environment. In-depth knowledge of current agentic AI technologies and a strong software development background. Expertise in building high-performance AI applications that integrate a multitude of data sources. Excellent problem-solving, system design skills, and the ability to drive technical alignment across teams. MS or PhD in a science or engineering field. Experience in building and maintaining scalable, big data applications in a cloud environment.