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EnCharge AI

Analog in-memory AI hardware and software

Principal Solutions Engineer

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$200k - $250k /yrRemote

About the Job

Requirements

  • At least 8 years of experience in Solutions Engineering, Field Applications Engineering, Technical Marketing Engineering, or related customer-facing technical roles within the semiconductor or artificial intelligence industry.
  • A proven track record of bringing complex hardware and software products to market and driving adoption through end-to-end solution integration.
  • Strong software development experience using Python and C++.
  • Hands-on experience with artificial intelligence and machine learning frameworks such as PyTorch, TensorFlow, or ONNX Runtime, as well as artificial intelligence inference optimization and model deployment.
  • Strong understanding of artificial intelligence workloads, optimization, heterogeneous system-on-chip architectures, software stacks, and system integration.
  • Experience working with embedded Linux systems, heterogeneous compute platforms, or artificial intelligence accelerators.
  • Ability to explain complex technical concepts clearly to diverse technical and executive audiences.
  • A self-motivated, execution-oriented approach with a strong customer-first focus on solving complex technical challenges.

Responsibilities

  • Serve as the primary technical interface and trusted advisor for strategic customers and partners evaluating and deploying artificial intelligence workloads on EnCharge platforms.
  • Lead end-to-end customer engagements from technical discovery through proof-of-concept, design-in, performance benchmarking, system-level tuning, and production deployment.
  • Support technical pre-sales efforts by articulating solution value propositions, architectural differentiators, and competitive performance benchmarks.
  • Architect and develop reference applications, demonstrations, solution accelerators, and customer evaluation platforms for diverse verticals, including edge artificial intelligence, robotics, autonomous systems, and enterprise datacenters.
  • Help customers integrate complex artificial intelligence models, perception pipelines, multimodal systems, artificial intelligence agents, and software stacks into robust end-to-end solutions.
  • Identify and onboard strategic software and hardware partners, mapping value chains to co-develop artificial intelligence solutions that expand market reach and accelerate time to market.
  • Collaborate with original design manufacturers on complete system designs and with independent software vendors to deliver documentation and reference designs for the ecosystem.
  • Troubleshoot complex hardware and software integration challenges, optimizing application performance, latency, throughput, and power efficiency.
  • Partner with Product Management and Engineering to communicate requirements, identify product gaps, and influence the product roadmap.
  • Develop technical documentation, application notes, tutorials, training materials, and enablement collateral.

Desired Qualifications

  • Knowledge of artificial intelligence agents, agentic workflows, multimodal artificial intelligence systems, or large language model-based edge applications.
  • Background in computer vision, autonomous navigation, perception systems, or embedded industrial automation.
  • Experience delivering technical training or speaking at customer workshops and industry conferences.

About the Company

EnCharge AI

Analog in-memory AI hardware and software

EnCharge AI designs and sells AI-accelerating hardware and software for edge-to-cloud workloads, focusing on analog in-memory computing. Its products include chiplets, ASICs, PCIe cards, and flexible software that integrates across platforms. The approach uses semiconductor design to implement analog in-memory computing for fast AI processing with lower power and smaller footprint, compatible with existing systems. Compared with competitors, it prioritizes sustainability with lower CO2 emissions and total cost of ownership, backed by a leadership team with 20+ years in AI hardware and a track record of 350 million chips shipped, 150 patents, and 300 publications, and aims to democratize advanced AI by making it affordable and environmentally sustainable.

Company size
51-200
Company stage
Series B
Total funding
$162.9M
Headquarters
Santa Clara, CA
Founded
2022

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