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AVP Sales; Data​/AI Hitech

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Jobs via Dice
Full Time position
Listed on 2026-03-13
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: AVP Sales (Data/AI) For Hitech

Dice is the leading career destination for tech experts at every stage of their careers. Our client, RIIASH LLC, is seeking the following. Apply via Dice today!

Role Summary

The AVP – Sales (Data, Analytics, Integration & AI) will own revenue growth, client acquisition, and portfolio expansion for the Hitech clients
. This is a high‑visibility, quota‑carrying executive role responsible for leading enterprise consultative sales across Data Modernization, Data Engineering, Analytics, API‑led Integration, AI/ML, and Generative AI platforms. You will work closely with industry leaders, Chief Data Officers, CIOs, CMOs, Digital & AI executives to position Persistent as a strategic partner for data‑driven transformation.

Required
  • 12–18 years of sales leadership experience in Data, Analytics, Integration, AI/ML within IT services or consulting firms.
  • Proven success selling to the Hitech industry, managing large deals with annual revenue portfolios.
  • Strong understanding of:
    • Enterprise Data Architecture & Cloud Data Platforms
    • API‑led & Event‑driven integration
    • Advanced analytics & ML/AI models
    • GenAI, LLMOps, AI governance & AI transformation programs
  • Demonstrated ability to lead complex consultative sales cycles across Fortune 1000 organizations.
Preferred
  • Prior experience working with hyperscaler ecosystems or modern data platforms.
  • Exposure to agentic AI systems, AI‑infused workflows, or next‑gen customer experience solutions.
  • MBA or equivalent is a plus.
SUCCESS METRICS
  • Annual revenue and booking goals
  • Net‑new logos and multi‑year deal wins
  • Expansion of Hitech accounts across data & AI towers
  • Pipeline health, conversion rates, forecasting accuracy
  • Client satisfaction and retention
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