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Software Engineer - AI Platform

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Rivian VW Group
Full Time position
Listed on 2026-06-12
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Staff 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.

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.

Role Summary

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 r 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 production‑grade tools are scalable, reliable, and maintainable across the organization.

Responsibilities
  • Architect and Own Agentic Systems at Org‑Wide Scale: 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.

  • Define LLM Integration Strategy: 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.

  • Lead the Cognitive Automation

    Roadmap:

    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.

  • Champion Scalable System Design: 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.

  • Establish and Uphold Engineering Standards Across the Organization: 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.

  • Drive Technical Consensus and Shape Organizational Direction: 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.

  • Lead Cross‑Functional Alignment at the Executive Level: 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.

  • Grow and Elevate Engineering Talent Broadly: 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.

Qualifications
  • Advanced Degree: Bachelor's, Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related field.

  • Proven Experience: 12+ years of hands‑on experience in software engineering, with a deep…

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