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AV-ADAS Technical GTM Specialist, WWSO HPC Team

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Amazon
Full Time position
Listed on 2026-05-29
Job specializations:
  • IT/Tech
    Systems Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Overview

The automotive industry is undergoing a structural shift toward Software-Defined Vehicles (SDV). Automotive OEMs are taking direct ownership of their software stacks through internal software factories. This creates new buyer personas, new technical requirements, and significant opportunity for cloud-native development on AWS.

AWS is seeking a technically deep, business‑minded Automotive Compute Tech GTM Specialist to join the Worldwide Specialist Organization (WWSO) HPC team. You will own the end‑to‑end GTM strategy for AWS's automotive compute portfolio spanning Autonomous Vehicles (AV), Advanced Driver Assistance Systems (ADAS), Software‑Defined Vehicle (SDV), and Electrical/Electronic (E/E) architecture workloads.

In this tech BD role, you will drive acceleration of the revenue pipeline, convert pipeline into launch revenue, and build the mechanisms that turn technical engagement into measurable business outcomes. You own the strategy, the technical discussion and execution. You will work directly with customers: C‑level and VP‑level stakeholders at leading OEMs and Tier‑1 suppliers, and build partner enablement strategies that scale customer adoption.

You will collaborate closely with the Automotive Industry Business Unit (IBU) and serve as a visible AWS specialist with technical depth with industry‑level go‑to‑market strategy to maximize customer impact.

Key Job Responsibilities
  • Own the AV‑ADAS HPC GTM strategy end‑to‑end, with full accountability for pipeline, launch revenue, and business outcomes
  • Drive GTM motions for AV, ADAS, SDV, and E/E workloads across AWS's global automotive customer base in partnership with the Automotive IBU
  • Identify, qualify, and advance opportunities from technical engagement through to closed revenue; build mechanisms that compress sales cycles and increase win rates
  • Build and execute a partner enablement strategy that scales customer adoption through technology and consulting partners
  • Develop GTM plays tailored to OEM Software Factories, domain controller architectures, and repositioned Tier‑1 suppliers. Evangelize cloud‑native development environments and engineering workbenches for ADAS/AV/SDV workflows
  • Articulate the value of Generative AI in accelerating automotive software development
  • Collaborate cross‑functionally with the Automotive IBU, AWS service teams, Solutions Architects, partner teams, and product teams
  • Build scalable technical content, reference architectures, workshops, and enablement materials to accelerate adoption
Basic Qualifications
  • Experience engaging and influencing senior executives, demonstrating a strong familiarity with decision‑making processes in enterprise customers
  • 7+ years of experience in automotive software, with deep knowledge of ADAS, AV, SDV, or E/E architecture development. Strong understanding of in‑vehicle software development life cycles including tool chains, HPC simulation, validation, and deployment
  • Proven track record driving revenue pipeline from technical engagement through to closed business. Experience developing and executing GTM strategies for technical products or cloud services
  • Excellent written and verbal communication skills; able to translate technical concepts for both business and technical audiences
  • Master's degree in Computer Science, Electrical Engineering, Automotive Engineering, or a related field (or equivalent experience)
Preferred Qualifications
  • Advanced degree in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields
  • Prior experience in an AV‑ADAS or industry vertical team at a hyperscaler or large technology company. Deep understanding of distributed ML framework and HPC infrastructure and distributed system.
  • Hands‑on experience with cloud‑based virtual engineering workbenches, simulation platforms, or digital twin environments
  • Familiarity with FPGA‑based development, RISC‑V architectures, or embedded hardware emulation in cloud environments. Knowledge of AUTOSAR (Classic and Adaptive) and automotive data pipelines including sensor data, V2X, and fleet telemetry
  • Deep knowledge of the automotive partner ecosystem including toolchain vendors, middleware providers,…
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