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 6 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.

We are seeking a highly motivated AI Engineer to join our team and help us accelerate software innovations for next-generation software-defined vehicles. In this role, you will be responsible for high-quality implementation of an Agentic Framework to support our AI applications. You will be responsible for writing the production-grade code that allows our AI applications to interact with millions of vehicles in real-time. We need a "builder" who thrives on the technical details of multi-agent orchestration, tool-calling optimization, and LLM security. You will translate architectural designs into executable, high-performance systems, taking full ownership of the development lifecycle from local prototyping to global cloud deployment. This is a hands-on role for an engineer who prioritizes execution, code quality, and system reliability for multi-agent systems, AI technologies and platforms.

This is a hybrid role based in our Dublin, IE office, where you will be expected to work in our office 3 days a week.

Duties and Responsibilities

Lead efforts to leverage existing AI models and frameworks to solve complex business challenges.
Develop agentic orchestration by designing and implementing reason and act loops that allow AI agents to decompose complex goals into actionable sub-tasks.
Design and implement a versioned prompt registry allowing for model-agnostic routing and A/B testing of system prompts
Engineer the privacy shield for PII redaction and the hallucination verifier to audit AI-generated actions before execution
Conduct the full cycle of data modeling and algorithm development, including modeling, training, tuning, validating, deploying, and maintaining services, (AI breadth).
Strong domain expertise in the AI area including LLM, Time Series, RAG, fine-tune large models, traditional ML models, etc. (AI depth)
Stay current with industry trends and advancements in data science and AI technologies. (State-of-the-Art)
Perform data analysis and offer insights to inform business decisions across multiple domains.
Adhere to data privacy and security protocols to uphold the confidentiality of sensitive information.
Collaborate with cross-functional teams to understand requirements and translate them into effective AI and data science solutions.
Document and communicate technical designs, processes, and best practices to stakeholders using visualizations and presentations.
Take charge of projects, ensuring timely completion in a dynamic work environment.

Qualifications and Experience

Master’s or PhD in Computer Science, Engineering, Mathematics, Applied Sciences, or a related field preferred. Bachelor's degree required.
Strong programming skills in languages such as Golang, Python, Java, or C++, with hands-on experience in relevant frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Proven experience building multi-agent systems and frameworks with adaptive orchestration
Deep understanding of Jailbreak Detection (e.g., LlamaGuard) and PII masking techniques to ensure safe LLM interactions in regulated environments
In-depth knowledge and understanding of current machine learning algorithms, AI technologies, and platforms.
Solid experience in data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
Strong knowledge of software development best practices, version control systems, and agile methodologies.
Results-driven with a positive can-do attitude and excellent problem-solving skills.
Exceptional verbal and written communication skills, with the ability to collaborate effectively with cross-functional teams.
Experience in the automotive industry is highly desirable.

Senior AI Engineer

Job Description