Full-Time

Staff DFT Engineer

Updated on 6/25/2026

EnCharge AI

EnCharge AI

51-200 employees

Analog in-memory AI hardware and software

No salary listed

Bengaluru, Karnataka, India

In Person

Category
Hardware Engineering (1)
Requirements
  • 9–10 years of hands-on experience in DFT, preferably with at least one full tape-out cycle in a lead or staff capacity.
  • Expert-level proficiency with industry-standard tools (e.g., Siemens Tessent, Synopsys DFTMAX/TetraMAX, or Cadence Genus/Modus).
  • Deep understanding of DFT-centric STA, power-aware DFT, and high-speed IO testing.
  • Startup mindset: You are comfortable wearing multiple hats. You don't wait for a manual; you build the manual.
  • Edge AI Interest: A genuine interest in how AI hardware differs from general-purpose CPUs/GPUs.
Responsibilities
  • End-to-End DFT Strategy: Define and implement the complete DFT architecture as independent as possible, including Scan, MBIST, BSCAN, and Boundary Scan.
  • Constraint Management: Take charge of DFT constraint development and management, ensuring seamless integration with synthesis and STA teams.
  • ATPG & Simulation: Generate high-coverage test patterns (Stuck-at, At-speed, Transition, Path Delay) and lead the verification of these patterns through timing-annotated simulations.
  • AI-Specific Optimization: Implement advanced DFT techniques tailored for Edge AI architectures, such as high-bandwidth memory testing and low-power test modes.
  • Hierarchical DFT: Design and execute hierarchical DFT flows to manage complexity in large-scale AI SOCs.
  • Silicon Bring-up: Partner with the ATE (Automated Test Equipment) teams to debug patterns on silicon and drive yield improvement initiatives.

EnCharge AI develops hardware and software for artificial intelligence computation, ranging from edge devices to cloud servers. The company utilizes analog in-memory computing through chiplets, ASICs, and PCIe cards to process AI tasks directly within memory, which reduces the power and space required for complex calculations. Unlike competitors using traditional digital methods, EnCharge AI offers significantly lower CO2 emissions and a lower total cost of ownership by integrating its specialized technology into the existing semiconductor supply chain. The company's goal is to democratize advanced AI by making it economically viable and sustainable for businesses to solve large-scale human challenges.

Company Size

51-200

Company Stage

Series B

Total Funding

$162.9M

Headquarters

Santa Clara, California

Founded

2022

Your Connections

People at EnCharge AI who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Samsung and Foxconn funding enables consumer electronics supply chain integration.
  • RTX Ventures accelerates defense adoption overcoming power constraints.
  • Enterprise edge AI demand surges for privacy and low-latency processing.

What critics are saying

  • Nvidia CUDA lock-in captures 70-85% edge market share in 12-24 months.
  • Samsung prioritizes internal analog chips over EnCharge partnerships in 6-12 months.
  • Analog precision fails multi-layer scaling, burns $144M cash by mid-2026.

What makes EnCharge AI unique

  • EN100 accelerator uses analog capacitors for 20x performance-per-watt over GPUs.
  • Capacitor-based in-memory computing integrates into existing CMOS processes seamlessly.
  • Princeton spinout delivers 150 TOPS at 1 watt for edge AI inference.

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Benefits

Health Insurance

401(k) Retirement Plan

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

5%

2 year growth

1%
Electronics For You
Sep 23rd, 2025
Run Advanced AI Locally On Laptops and Workstations

EnCharge AI has introduced the EN100 accelerator to run AI inference directly on local devices.

StartupHub.ai
May 31st, 2025
EnCharge AI Raises $144M for Chips

EnCharge AI, an AI chip startup from Princeton University, has raised $144 million to advance its analog in-memory computing technology. Their EN100 AI accelerator chip offers improved performance per watt, enabling advanced AI on laptops and edge devices while reducing energy use. The funding will help expand their technology and software suite. Investors include Tiger Global, Samsung Ventures, and others. The company is poised for growth in the AI PC and edge device market.

The Associated Press
Apr 17th, 2025
EnCharge AI Expands Leadership After $100M Series B

EnCharge AI has appointed Jason Huang as VP of Finance and Leslie Szeto as Director of HR following a $100 million Series B funding round. Huang will enhance financial strategy for growth, while Szeto will focus on talent acquisition and organizational development. These hires support EnCharge's transition from development to commercialization of its AI accelerator products. Huang and Szeto bring extensive experience in high-growth transitions, IPOs, and acquisitions.

TechNews
Feb 18th, 2025
EnCharge AI secures $100M for AI chip

EnCharge AI has secured over $100 million in a Series B funding round, bringing its total funding to over $144 million. The company is developing a new AI accelerator chip that aims to match desktop GPU performance with only 1% of the power consumption. Their chip, which uses analog capacitors for computation, is expected to launch later this year for mobile devices, PCs, and workstations, with commercialization planned for 2025.

eeNews Europe
Feb 14th, 2025
EnCharge AI raises $100m from Samsung, Foxconn

EnCharge AI raises $100m from Samsung, Foxconn.