Architect, develop, and deploy end-to-end agentic full-stack Generative AI (GenAI) applications that solve complex real-world problems, with a specific focus on improving engineering challenges and inefficiencies. Design and implement robust, scalable data science and Machine Learning Operations (MLOps) pipelines primarily within cloud environments like Google Cloud Platform (GCP) and Amazon Web Services (AWS), ensuring efficient deployment and maintenance of AI solutions. Lead the integration of new cloud technologies and AI tools (e.g., Vertex AI) into our workflows, continuously evaluating their potential and articulating their business value to drive innovation and efficiency. Develop intuitive and responsive front-end user interfaces that enable seamless interaction with agentic AI systems and effectively translate complex outputs into actionable insights. Acquire a deep understanding of vehicle engineering problems, translating them into appropriate mathematical representations and AI/ML solutions (classification, prediction, intelligent automation). Ensure the overall quality and integrity of data and solutions throughout the development lifecycle, from data collection and cleaning to model deployment. Established and active employee resource groups Bachelor's Degree in Computer Science & Engineering or equivalent combination of relevant education and experience. 3+ years of experience building full-stack applications in production environments, with proficiency in JavaScript/TypeScript, React, HTML and backend frameworks including Next.js, Node.js, Python, or Go 2+ year experience with database systems (SQL, NoSQL), API design (REST/GraphQL) and building scalable API services using frameworks such as Flask or FastAPI. 2+ year experience deploying and maintaining applications in cloud-native environments (e.g., AWS, Azure, GCP) 2+ year experience working with DevOps tools (Docker, Kubernetes, Terraform, etc.) Leveraging and integrating cloud-based AI tools like Vertex AI into production systems. A strong passion for evaluating, championing, and integrating new technologies and tools, particularly within GCP, into existing workflows, with the ability to clearly articulate and justify their business value and impact. Exceptional collaboration skills, with the ability to effectively interface between technical development teams and business stakeholders, understanding and navigating both IT and business constraints. Comfortable working in ambiguous environments where problems are not always well-defined, and solutions require innovative thinking. Masters Degree in Computer Science & Engineering Advanced data manipulation and analysis using libraries such as Pandas. Machine Learning model development, including Natural Language Processing (NLP), and utilizing deep learning frameworks like PyTorch, TensorFlow, and Keras. 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). 3+ years of Front-End Development experience using modern web technologies like React, JavaScript, and HTML, to build intuitive user interfaces for AI applications.