Senior Software Engineer, AI Platform

About Us

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world.

The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone.

As a Senior Software Engineer specializing in agentic applications, you will be a key technical leader and influential voice in shaping our GenAI platform's architecture and strategy. You will play a pivotal role in integrating LLMs with our internal and customer-facing applications r focus will be on leveraging LLMs to drive cognitive automation, streamlining workflows, and enhancing decision-making. You'll also pioneer and evangelize best practices in building resilient, scalable, and observable distributed systems, ensuring production-grade tools that are scalable, reliable, and maintainable across the organization.

• Architect Design of Agentic Systems: Architect and lead the development of highly scalable and sophisticated intelligent agents that utilize LLMs to automate workflows, optimize operations, and elevate user experiences across our internal and customer-facing applications.
• Shape LLM Integration Strategy: In partnership with your peers, help define and drive the technical vision and long-term strategy for integrating LLMs with our evolving software ecosystem, ensuring robust, scalable, and maintainable communication and data exchange.
• Drive the Cognitive Automation
  
  Roadmap:
  
  Collaborate with product managers and other technical leaders to identify and prioritize high-impact opportunities for cognitive automation. Leverage LLMs to automate complex cognitive tasks, such as information extraction, summarization, and question answering, to enhance efficiency and accuracy system-wide.
• Champion Scalable System Design: Take ownership of the entire development lifecycle, from conceptualization and design to implementation and deployment, for our most critical machine learning-powered tools and applications.
• Establish and Uphold Engineering Best Practices: Define, implement, and enforce industry-leading standards for building production-grade, distributed machine learning solutions, ensuring scalability, reliability, and maintainability.
• Drive Technical Consensus and Influence Direction: Continuously research and experiment with emerging trends in machine learning, AI agents, and distributed systems.
• Collaborate and Lead Cross-Functionally: Work closely with Machine Learning engineers, product teams, and senior leadership to gather requirements, define project scope, and deliver impactful solutions. Drive technical alignment across multiple teams.
• Mentor and Develop Technical Talent: Share your expertise and provide guidance to senior engineers and technical leads, fostering a culture of technical excellence, innovation, and continuous learning.

• Advanced Degree: Bachelor's, Master's degree or Ph.D. in Computer Science, Machine Learning, or a related field.
• Proven Experience: 8+ years of hands‑on experience in software engineering, with a deep focus on designing and building large‑scale distributed systems. Extensive, hands‑on experience in building and deploying complex agentic applications leveraging LLMs in production environments.
• Strong Technical
  
  Skills:
  
  Expertise in Golang is strongly preferred. Proficiency in Python or similar programming languages, as well as deep expertise with cloud and container frameworks such as AWS and Kubernetes. A proven track record of designing and building highly scalable, fault‑tolerant, and observable distributed systems.
• Deep Understanding: Expert‑level grasp of machine learning principles, algorithms, and evaluation metrics, as well as software engineering best practices for distributed systems.
• Production
  
  Expe…