Senior Staff Customer Engineer – Automotive AI Engineer

🕒 April 2

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Sonatus

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

☁️ SaaS

💰 $75M Corporate Round on 2022-12

Automotive • Artificial Intelligence • SaaS

Sonatus is a leading vehicle software company that specializes in accelerating the transition to software-defined vehicles (SDVs). The company provides in-vehicle and cloud software that enables automakers to innovate rapidly and improve capabilities, reliability, and user experience throughout the vehicle lifespan. Sonatus offers a range of solutions including Sonatus Vehicle Platform, Sonatus Foundation, Collector AI, Automator AI, Guard, and Updater, all designed to enhance vehicle software architecture, data collection, security, and over-the-air (OTA) updates. With a focus on the automotive industry, Sonatus partners with companies to deliver innovative end-to-end solutions that support various vehicle types, including passenger and commercial vehicles. The company has achieved AWS Automotive Competency Status and continues to provide cutting-edge technology for the SDV era.

📋 Description

• Partner with automotive OEMs and Tier 1 suppliers to identify, shape, and prioritize high-impact AI-driven use cases, guiding customers toward scalable and high-leverage solutions • Act as a trusted advisor to customers by shaping problem definition, challenging assumptions, and guiding technical decision-making toward scalable AI solutions • Drive alignment and adoption of solutions by clearly articulating trade-offs, ROI, and long-term architectural implications to technical and executive stakeholders • Design, integrate, and deploy AI/ML-based solutions across cloud and in-vehicle environments, enabling end-to-end vehicle-to-cloud use cases with reliable data flow and system interoperability • Develop and iterate AI models, PoCs, and production-ready solutions, continuously improving performance based on real-world data and customer feedback • Lead technical discussions and solution reviews focused on AI feasibility, model performance, trade-offs, and system limitations • Identify risks related to AI deployment and integration (e.g., data availability, security constraints, model reliability) and drive mitigation strategies • Collaborate with internal teams (AI Platform, Product, Engineering) to enhance AI capabilities, model deployment pipelines, and platform scalability

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or PhD preferred) • 12+ years of experience in AI / Machine Learning, Data Engineering, or related domains, with exposure to automotive software or vehicle systems • Solid understanding of machine learning, data analytics, and AI-based systems, including practical experience delivering real-world solutions • Experience designing and working with data pipelines, analytics workflows, and model-driven systems • Strong experience deploying and operating software in cloud environments (AWS, Azure, GCP, or customer-managed infrastructure) • Experience integrating platform-based solutions with external systems, data pipelines, and APIs • Familiarity with containerization and deployment technologies such as Docker and Kubernetes • Strong hands-on experience developing, integrating, and deploying AI/ML-based solutions in production environments • Proven ability to influence customer direction and drive technical decision-making in customer-facing engagements • Experience leading technical discovery, shaping ambiguous problem spaces, and proposing scalable solution approaches • Proven ability to communicate complex technical concepts clearly and persuasively to both technical and non-technical stakeholders • Ability to operate effectively in ambiguous environments and drive clarity, alignment, and execution • Experience in customer engineering, solution engineering, or forward-deployed engineering roles is highly preferred • Familiarity with modern AI methodologies such as Agentic AI, Retrieval-Augmented Generation (RAG), or data-driven automation is a plus.

🏖️ Benefits

• • • • • •