Staff Software Engineer - AI Platform

Rivian and Volkswagen Group Technologies•Palo Alto, CA

1d•$206,500 - $258,100

About The Position

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. Rivian and Volkswagen Group Technologies Canada is proud to be a Great Place To Work® Certified company — 92% of employees at RV Tech Canada say it is a great place to work, compared to 60% at a typical company. As a Staff Software Engineer specializing in agentic applications, you will be a defining technical authority and highly influential voice in shaping our GenAI platform's architecture and strategy. You will play a foundational role in integrating LLMs with our internal and customer-facing applications at scale. Your focus will be on leveraging LLMs to drive cognitive automation, streamlining workflows, and enhancing decision-making. You'll also set the standard for best practices in building resilient, scalable, and observable distributed systems, ensuring the creation of production-grade tools that are scalable, reliable, and maintainable across the entire organization.

Requirements

Bachelor's, Master's degree or Ph.D. in Computer Science, Machine Learning, or a related field.
12+ 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.
Demonstrated track record of org-wide technical impact.
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.
Expert-level grasp of machine learning principles, algorithms, and evaluation metrics, as well as software engineering best practices for distributed systems.
Demonstrated success in owning the design, deployment, and operation of scalable backend software in high-stakes production environments at significant organizational scale.
Excellent communication and teamwork skills, with a proven ability to build consensus with executive stakeholders, define engineering culture, and align entire organizations on complex technical decisions.
A genuine interest in exploring the latest advancements in machine learning and natural language processing and applying them to solve impactful business challenges at scale.

Responsibilities

Architect and lead the development of highly scalable and sophisticated intelligent agents that utilize LLMs to automate workflows, optimize operations, and elevate user experiences — setting the technical direction across multiple teams and product areas.
Own 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. Serve as the primary technical decision-maker and escalation point for LLM architecture across the organization.
Partner with product managers, engineering leaders, and senior leadership to set the strategic direction 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.
Take ultimate 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 technical frameworks and patterns adopted org-wide.
Define the engineering culture. Implement and enforce industry-leading standards for building production-grade, distributed machine learning solutions — and ensure adoption and consistency beyond your immediate team.
Continuously research and experiment with emerging trends in machine learning, AI agents, and distributed systems. Translate findings into actionable technical strategy with measurable org-wide impact.
Work closely with Machine Learning engineers, product teams, and senior leadership to gather requirements, define project scope, and deliver impactful solutions. Own technical alignment across the organization and represent engineering at the executive level.
Share your expertise and provide guidance across engineering levels — from mid-level engineers to senior leads — fostering a culture of technical excellence, innovation, and continuous learning. Actively contribute to hiring strategy and technical bar-raising.