Role Description
Sonatus is seeking a highly motivated, experienced AI Engineer to join our Customer Engineering (CE) team and help deliver AI-driven solutions for automotive OEM and Tier-1 customers. In this role, you will work directly with customers to understand real-world challenges in their vehicle environments and translate those challenges into practical solutions using Sonatus AI technologies.
A key responsibility of this role is to integrate and deploy AI capabilities on top of the Sonatus AI platform within cloud environments (Sonatus or customer-managed) while ensuring seamless interaction with vehicle-side systems and data. This position operates in a forward-deployed engineering model, working closely with customer engineering teams to deliver end-to-end solutions from problem definition to deployment.
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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.
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Act as a trusted advisor to customers by shaping problem definition, challenging assumptions, and guiding technical decision-making toward scalable AI solutions.
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Drive alignment and adoption of solutions by clearly articulating trade-offs, ROI, and long-term architectural implications to technical and executive stakeholders.
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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.
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Develop and iterate AI models, PoCs, and production-ready solutions, continuously improving performance based on real-world data and customer feedback.
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Lead technical discussions and solution reviews focused on AI feasibility, model performance, trade-offs, and system limitations.
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Identify risks related to AI deployment and integration (e.g., data availability, security constraints, model reliability) and drive mitigation strategies.
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Collaborate with internal teams (AI Platform, Product, Engineering) to enhance AI capabilities, model deployment pipelines, and platform scalability.
Qualifications
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Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or PhD preferred).
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12+ years of experience in AI / Machine Learning, Data Engineering, or related domains, with exposure to automotive software or vehicle systems.
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Solid understanding of machine learning, data analytics, and AI-based systems, including practical experience delivering real-world solutions.
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Experience designing and working with data pipelines, analytics workflows, and model-driven systems.
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Strong experience deploying and operating software in cloud environments (AWS, Azure, GCP, or customer-managed infrastructure).
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Experience integrating platform-based solutions with external systems, data pipelines, and APIs.
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Familiarity with containerization and deployment technologies such as Docker and Kubernetes.
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Strong hands-on experience developing, integrating, and deploying AI/ML-based solutions in production environments.
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Proven ability to influence customer direction and drive technical decision-making in customer-facing engagements.
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Experience leading technical discovery, shaping ambiguous problem spaces, and proposing scalable solution approaches.
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Proven ability to communicate complex technical concepts clearly and persuasively to both technical and non-technical stakeholders.
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Ability to operate effectively in ambiguous environments and drive clarity, alignment, and execution.
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Experience in customer engineering, solution engineering, or forward-deployed engineering roles is highly preferred.
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Familiarity with modern AI methodologies such as Agentic AI, Retrieval-Augmented Generation (RAG), or data-driven automation is a plus.