Staff Technical Program Manager, AI & Data

Rivian and Volkswagen Group Technologies•Irvine, CA

1d•$167,400 - $209,300

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. Our Data & AI team is looking for a Staff Technical Program Manager to drive cross-functional, strategic Data & AI initiatives across the organization. This role requires a high level of initiative, independent judgment, and indirect leadership. You'll operate as the connective tissue across product, platform, and infrastructure teams — translating ambiguous, technically complex Data & AI efforts into clear plans, dependencies, and delivery commitments. Projects in scope may be product-oriented (customer-facing AI/data features), platform-focused (the data and ML infrastructure other teams build on), or internal-facing (tooling and systems that improve how the company uses data and AI). You will be expected to flex across all three, often on the same project, and to bring both program rigor and enough technical fluency to be credible with the engineers, data scientists, and ML practitioners you're coordinating.

Requirements

Demonstrated experience serving as TPM for Data & AI projects specifically — this is a hard requirement, not a nice-to-have.
8+ years of Technical or Engineering Program Management experience.
BS or MS in Computer Science, Data Science, Engineering, or another related technical field.
Basic understanding of the Data Engineering stack, with familiarity with tools such as Databricks, Hex, or similar.
Comfortable and proficient with AI tools such as Cowork, Gemini, and Codex, with demonstrated experience building your own TPM productivity tools using these tools (e.g., automating status reporting, risk tracking, or documentation workflows).
Willingness and enthusiasm to use AI tools as part of day-to-day program management work (not just programs about AI).
Proven ability to operate effectively in highly technical, ambiguous environments, and to earn credibility with engineers, data scientists, and ML practitioners.
Proven experience working in a rich cross-functional setting, coordinating across many stakeholder groups, competing priorities, and organizational boundaries with minimal direct authority.
Excellent communication, organizational, and cross-functional collaboration skills, including with executive stakeholders.
Experience with agile and waterfall development processes using Jira or similar program management tooling.
Proven track record planning budgets, maintaining forecasts, and managing risk registers across multiple concurrent programs.
Strong team player known for building trust and partnering across functional lines.

Responsibilities

Own end-to-end delivery for strategic Data & AI programs spanning product, platform, and internal-facing initiatives, from scoping through launch and post-launch health.
Plan, create, and maintain technical schedules, priorities, and execution plans across multiple Data & AI workstreams that cross organizational boundaries.
Drive broad, deep cross-functional programs internally and, where relevant, with external partners or vendors.
Partner with and influence Data Engineering, ML/AI, Analytics, Platform, and Product teams — including leadership — to align on scope, sequencing, and trade-offs.
Identify programmatic and technical risk (data quality, model readiness, infra scaling, dependency slippage) early, and drive mitigation before it threatens timing.
Ensure technical designs for data pipelines, platforms, and AI/ML systems are properly evaluated for feasibility, scalability, and quality before commitments are made.
Expertly manage stakeholder expectations, proactively surfacing dependencies and risks rather than waiting to be asked.
Provide program and executive-level status updates, and run healthy escalations ahead of deliverables going out of bounds.
Identify and drive continuous process improvements in how Data & AI programs are planned, tracked, and delivered.
Model and encourage practical use of AI tools within the program management workflow itself (e.g., status synthesis, documentation, risk analysis).