AI Engineer

AI Engineer

Location
- Sunnyvale, CA - (Hybrid – 3 Days Per Week)

Compensation - $225,000 – $300,000 Base + Competitive Equity

Visa
- Visa Sponsorship Available

Company Stage
- Growth Stage ($110M+ Raised)

Industry
- Artificial Intelligence, Machine Learning, Autonomous Systems, Automotive Software, Software-Defined Vehicles, Edge AI, Enterprise Software

The company is building the software platform powering the next generation of software-defined vehicles by bringing cloud-native software, artificial intelligence, and over-the-air infrastructure into the automotive industry.

Its platform enables global automotive manufacturers to collect vehicle data, deploy intelligent software updates, optimize vehicle operations, and build AI-powered applications that continuously improve vehicle performance. With millions of connected vehicles already running its software, the company is helping redefine how modern vehicles are developed, maintained, and enhanced through AI.

Backed by more than $110M in funding and trusted by one of the world's largest automotive manufacturers, the company has grown into one of the leaders in software-defined vehicle infrastructure while continuing to expand its AI product portfolio through cutting-edge LLM applications, agentic AI systems, and intelligent edge computing.

As an AI Engineer, you'll join the Office of the CTO to prototype, develop, and product ionize next-generation AI capabilities across LLMs, RAG systems, agentic workflows, and machine learning platforms while partnering directly with executive leadership to define the company's future AI roadmap.

This is an exceptional opportunity to join an AI-native innovation team where engineers own AI products from concept through production, influence company-wide technical strategy, and build cutting-edge AI systems powering the future of connected vehicles.

• Lead development of AI-powered software solutions solving complex real-world business problems
• Design and build production-ready applications using LLMs, RAG architectures, and agentic AI frameworks
• Develop proof-of-concept AI products and evolve them into production-ready systems
• Design, train, fine-tune, validate, deploy, and maintain machine learning models
• Evaluate emerging large language models and identify optimal architectures for production use
• Build AI applications using Python, Tensor Flow, PyTorch, and modern AI frameworks
• Perform data analysis, feature engineering, and model evaluation across multiple AI domains
• Collaborate closely with Engineering, Product, and executive leadership to define future AI capabilities
• Optimize model inference, hardware utilization, and production AI performance
• Research emerging AI technologies and rapidly prototype innovative solutions
• Document AI architecture, technical design, and implementation decisions
• Continuously improve AI systems supporting next-generation software-defined vehicles

• 8–15 years of AI, Machine Learning, or Software Engineering experience
• Experience building production AI applications at AI-first or ML-driven companies
• Experience developing RAG systems, agentic AI frameworks, and LLM-powered applications
• Experience leading AI initiatives from concept through production deployment
• Experience building proof-of-concept systems and product ionizing new AI capabilities
• Experience operating as a Staff or Senior Staff Engineer preferred
• Experience working at startups or high-growth technology companies preferred
• Strong ownership mentality with demonstrated technical leadership
• Experience collaborating across AI research, engineering, and product organizations
• Experience building customer-facing AI applications with measurable business impact

• Strong Python software engineering experience
• Deep experience with Tensor Flow and/or Py Torch
• Experience building production LLM applications
• Strong understanding of Retrieval-Augmented Generation (RAG) architectures
• Experience with agentic AI frameworks and AI orchestration systems
• Strong machine learning fundamentals including model selection, evaluation, fine-tuning, and deployment
• Experience…