Sobre esta vaga de Senior Staff AI Engineer na Sonatus
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.
Role Summary:
We are seeking a Senior Staff AI Engineer with a combination of architectural expertise and production rigor to lead the development of an Agentic Framework to support our AI applications. In this role, you will be the technical anchor for our AI offerings, working to deliver a production-grade Agentic Operating Layer for software-defined vehicles.
This is a 50% Architecture / 50% Implementation position. You will be responsible for designing and implementing an extensible architecture that bridges high-velocity vehicle telemetry with sophisticated AI reasoning. We need a leader who is collaborative by nature but decisive in execution—someone who can drive architectural consensus and take full accountability for the performance, safety, and scalability of the resulting system.
Responsibilities:
- Lead the architecture and design of an extensible AI platform. Drive architectural consensus across teams on AI-core decisions to ensure platform unification.
- Lead the development of agentic orchestration by designing and implementing mission-critical components 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, 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.
- 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:
- Master’s or PhD in Computer Science, Engineering, Mathematics, Applied Sciences, or a related field preferred. Bachelor's degree required.
- 10+ years of software engineering experience with 4+ years dedicated to shipping production-scale AI/Agentic systems. You have a track record of moving projects from whiteboards to global cloud deployments.
- Strong programming skills in languages such as Python, Java, or C++, with hands-on experience in relevant frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Expert-level experience with stateful orchestration frameworks (e.g., LangGraph, AutoGen, or similar). You understand the nuances of managing state across complex, multi-step AI missions.
- Strong experience grounding AI in structured/unstructured Big Data environments. Practical knowledge of traditional databases, streaming analytics, and Vector databases.
- 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.
- Experience building multi-tenant "Platform-as-a-Service" (PaaS) models is desirable.
Benefits Offered:
- Competitive compensation and equity program
- Health care plan (Medical, Dental & Vision)
- Flexible and Dependent Care Expense program
- Retirement plan (401k)
- Life Insurance (Basic, Voluntary & AD&D)
- Unlimited paid time off per year, 15 paid holidays
- Hybrid office work arrangement/flexibility
Perk Offerings include:
- Complimentary lunches, snacks, and beverages during on-site working days
- Wellness benefit allowances (towards gym membership and fitness programs)
- Internet reimbursement
- Computer Accessory Allowance
Employee Engagement Offerings:
- Departmental team building and outings
- Employee Referral Program
- Culture/Employee Satisfaction Surveys - Feedback matters!
The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change.
