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Sonatus

No-code platform for software-defined vehicle development

Senior Manager - Engineering, AI Validation

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USA$240k - $290k

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field is required; a master's degree is preferred.
  • At least 10 years of software or systems engineering experience, including embedded, cloud, networking, security, or automotive domains, and at least 3 years leading engineering or quality assurance organizations.
  • Hands-on experience developing, deploying, testing, or operating AI/ML systems, with expertise in modern machine learning workflows, neural networks, and MLOps.
  • Deep understanding of large language models, retrieval-augmented generation architectures, vector databases, embeddings, retrieval optimization, and agentic AI frameworks such as LangGraph or equivalent orchestration platforms.
  • Experience designing and implementing scalable AI evaluation frameworks, including multi-step agentic workflows, regression testing, benchmarking, and automated quality scoring.
  • Expertise with hybrid evaluation methods combining deterministic validation, such as citation grounding, structural validation, and exact matching, with probabilistic LLM-as-a-Judge techniques such as faithfulness, answer relevance, context precision, and task completion.
  • Practical experience with retrieval-augmented generation evaluation frameworks such as RAGAS, including evaluation tuning, embedding optimization, retrieval quality improvement, and production-scale LLM evaluation pipelines.
  • Experience validating hallucination, grounding, citation accuracy, bias, fairness, toxicity, and factual consistency in production LLM applications.
  • Experience designing systems that verify external knowledge claims and ensure responses are grounded in traceable citations and trusted data sources.
  • Strong experience testing cloud-native platforms and cloud-managed embedded products, including end-to-end system validation.
  • Experience establishing AI governance, safety, compliance, and Responsible AI practices for enterprise or safety-critical systems.
  • Proficiency in Python, Linux, shell scripting, modern test frameworks including PyTest, Playwright, and Behave, and engineering productivity tools including Jenkins and JIRA.

Responsibilities

  • Define and drive the AI validation strategy across embedded, in-vehicle, cloud-connected, and cloud-native AI systems, identifying gaps in model development, testing, deployment, and governance.
  • Lead, hire, mentor, and grow a high-performing AI Validation organization, establishing scalable engineering processes, technical direction, and execution excellence.
  • Own end-to-end validation strategy for AI/ML models, LLMs, RAG pipelines, and agentic AI workflows, from data pipelines and model training through cloud services and in-vehicle deployment.
  • Architect and operationalize scalable evaluation frameworks and benchmarking platforms for AI systems, including multi-step agentic workflows, using deterministic metrics, LLM-as-a-Judge methodologies, automated regression testing, and production feedback loops.
  • Design and maintain evaluation harnesses for RAG and agentic systems that measure retrieval quality, grounding, citation accuracy, factual consistency, context relevance, safety, latency, reliability, and execution correctness.
  • Evaluate, integrate, and optimize open-source and commercial AI validation technologies, driving build-versus-buy decisions for the AI quality platform.
  • Establish AI governance, Responsible AI practices, model lineage, safety guardrails, and compliance processes appropriate for automotive safety-critical systems and enterprise AI products.
  • Act as the quality gatekeeper for AI-enabled releases, partnering with engineering, product, safety, and OEM stakeholders to identify risks, define release criteria, and ensure production readiness.
  • Collaborate across engineering teams to define validation strategies for emerging AI capabilities, rapidly prototype new evaluation approaches, and standardize successful practices into reusable frameworks.
  • Drive continuous improvement by tracking advances in AI evaluation, agentic AI, LLM validation, and RAG systems, and translating them into scalable validation capabilities.

Desired Qualifications

  • Experience validating AI or agentic systems in safety-critical or regulated industries such as automotive, aerospace, or medical.
  • A track record building and scaling an AI test/evaluation platform or developer experience used by multiple teams, including frameworks, reusable components, and reference implementations.
  • Demonstrated success moving AI testing practices from ad hoc methods to standardized, organization-wide adoption, with measurable impact on cycle time, quality, or reliability.
  • Experience implementing enterprise-grade AI governance, including auditability, monitoring, and policy enforcement, in production systems.
  • Deep experience evaluating LLM and RAG systems at scale, including agentic workflows, RAGAS-based evaluation, citation verification, hallucination detection, groundedness, faithfulness, answer relevance, tool/task correctness, and automated regression testing across offline and online feedback loops.

About the Company

Sonatus

No-code platform for software-defined vehicle development

Sonatus builds a no-code platform for software-defined vehicles that lets automakers design adaptable vehicle software architectures and evolve them over time. The platform uses data from vehicles throughout their lifespan to drive continuous improvements. It is used by major carmakers, such as Hyundai Motor Group, to collect real-time diagnostic data and iteratively improve vehicle quality and owner experience. The business targets the full vehicle lifecycle—from design and engineering to production and after-sales—providing a software building block that helps automakers innovate faster, cut costs, and boost reliability and user satisfaction. The company recently raised funding and is expanding globally, including entering the Japanese market, signaling growth potential in software-defined vehicle adoption.

Company size
201-500
Company stage
Series A
Total funding
$110M
Headquarters
Sunnyvale, CA
Founded
2018

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