Solutions Architect, Uber AI Solutions

Uber Uber · Consumer · Seattle, WA +2 · Product

This role is a Solutions Architect within Uber AI Solutions, focusing on pre-sales and technical wins for enterprise clients in Autonomous Systems, Robotics, and Generative AI. The role involves architecting and prototyping AI data solutions, translating customer needs into technical blueprints, and providing feedback to influence the product roadmap. It requires a strong understanding of the AI lifecycle and cross-functional delivery.

What you'd actually do

  1. Own the "Technical Win" by serving as the primary technical authority. This involves evaluating complex customer AI/ML data needs, translating them into rigorous Scopes of Work (SOWs) and Proof of Concepts (POCs), and documenting the end-to-end technical solution for commercial viability.
  2. Design and develop foundational "Solution Blueprints" for core industries (Autonomous Systems, Robotics, GenAI). Lead the technical design of scalable data and operational architectures, requiring hands-on work (e.g., Python) to build prototypes, unblock pilots, and create repeatable frameworks and technical playbooks.
  3. Act as a trusted technical advisor to senior leaders, translating Uber AI Solutions' capabilities into measurable business outcomes. This includes partnering with Sales and Program Managers and collaborating with global teams to ensure solutions are scalable and compliant with regulations (e.g., GDPR, CCPA).
  4. Act as the primary conduit for field intelligence. Distill unique customer requirements and market gaps into clear, actionable feature requests to directly influence and ensure the Uber AI Solutions product roadmap meets the evolving needs of advanced AI labs.

Skills

Required

  • 5+ years of experience leading technical programs in AI, Robotics, or Autonomous Systems, with a focus on cross-functional delivery.
  • Proven track record managing the end-to-end AI lifecycle, including data strategy, HITL workflows, and Generative AI deployments.
  • Expert at translating complex technical roadmaps into clear business outcomes and milestones for executive-level stakeholders.

Nice to have

  • Experience delivering AI data solutions across various regions and languages.
  • A sophisticated understanding of enterprise sales processes and GTM strategy.
  • Strong ability to navigate technical trade-offs and code-heavy environments (e.g., Python) to identify program risks and dependencies.
  • Experience with a hyperscaler or SaaS platform environment.

What the JD emphasized

  • high-stakes enterprise engagement
  • complex AI data challenges
  • hands-on work
  • code-heavy environments
  • AI lifecycle
  • Generative AI deployments
  • scalable and compliant with regulations

Other signals

  • enterprise engagement
  • AI data challenges
  • Generative AI
  • human-in-the-loop solution