Senior Account Executive, Uber AI Solutions

Uber Uber · Consumer · San Francisco, CA +1 · Sales & Account Management

This role is for a Senior Account Executive focused on selling Uber's AI Solutions, which include services for data collection, labeling, map editing, and AI model validation to enterprise customers. The role involves driving sales revenue, establishing go-to-market strategy, managing the sales lifecycle, and leveraging technical expertise to help customers meet their AI training data needs.

What you'd actually do

  1. Cultivate and sustain strong, multi-level relationships with various stakeholders from procurement and technical leaders to the C-suite to ensure smooth project delivery and drive account growth
  2. Drive revenue growth, expansion, and retention by executing strategic plans for your assigned account
  3. Generate and uphold precise weekly, monthly, and quarterly sales forecasts. This includes projecting revenue streams and identifying expansion opportunities across your accounts
  4. Maintain and update CRM data for performance tracking, pipeline management, and account status reporting
  5. Serve as the technology thought leader by leading co-creation initiatives to support your accounts and deliver on the roadmap

Skills

Required

  • B2B technology sales
  • SaaS
  • Cloud Infrastructure
  • AI/ML services
  • Consultative Selling
  • Value Engineering
  • draft complex SOWs
  • business cases
  • data labeling
  • HITL
  • Salesforce
  • Excel/Google Sheets

Nice to have

  • GenAI
  • Agentic AI workflows
  • RLHF
  • SFT
  • AI data solutions industry
  • data supply chain for machine learning
  • managing and expanding relationships within hyper-scale technology enterprises
  • accelerate sales cycles
  • start-up, scale-up or high-growth, entrepreneurial environment
  • interpersonal communication
  • presentation
  • negotiation
  • represent the company at industry gatherings

What the JD emphasized

  • 6+ years of experience in B2B technology sales
  • long-term sales cycles (6–18 months)
  • multi-stakeholder buy-in
  • Technical understanding of GenAI & Agentic AI workflows
  • expertise in techniques like RLHF and SFT etc.
  • Domain expertise within the AI data solutions industry
  • sophisticated understanding of the data supply chain for machine learning