---
title: 'Senior Emulation Engineer at EnCharge AI'
canonical: 'https://feeny.ai/job/senior-emulation-engineer-encharge-ai-india-0dxefhgwznrg'
type: 'job'
last_seen: '2026-09-12'
---

# Senior Emulation Engineer at EnCharge AI

- **Company:** EnCharge AI
- **Location:** India
- **Posted:** 2026-04-08
- **Last confirmed live:** 2026-09-12
- **Apply:** https://job-boards.greenhouse.io/enchargeai36/jobs/4212464009

## Job description

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

Senior Emulation Engineer

Location: India - Remote

Job Description:

At EnCharge AI, we are building the next generation of AI compute silicon — purpose-built

for high-performance, low-power, and scalable AI inference. As an Emulation Engineer, you

will play a critical role in validating complex AI accelerator architectures on emulation

platforms before tape-out. This position is ideal for someone passionate about bridging the

gap between hardware and software in fast-paced, deep tech environments.

Responsibilities:

- Set up and maintain Siemens Veloce emulation and prototyping platforms
- Adapt SoC designs for Emulation and Prototyping
- Develop and debug emulation testbenches and system-level environments
- Support pre-silicon validation, power/performance analysis, and early software bring-up. Participate in silicon bring-up and validation.
- Collaborate with design and verification teams to isolate design issues and accelerate debug.
- Optimize performance of the emulation workloads and reduce turnaround time.
- Work with firmware/software teams to enable use of emulators for OS and driver testing.

Required Background:

- BS/MS/Ph.D. in EE, CS, or related field with 7+ years of SoC design experience.
- Experience with emulation platforms (Veloce, Palladium, or ZeBu) and FPGA-based prototyping systems (proFPGA, HAPS, or Protium)
- Experience with emulating high speed I/O interfaces such as PCIe and UCIe and memory technologies such as LPDDR and HBM
- Solid understanding of digital design, RTL (Verilog/SystemVerilog), and SoC architecture.
- Proficiency in hardware debug tools, waveform viewers, and logic analyzers
- Scripting skills (e.g., Python, Tcl, Perl) for automation and infrastructure development
- Familiarity with UVM, simulation, and testbench environments. SystemVerilog and UVM-based verification experience a plus
- Hand-on software development experience with C/C++ is a plus

## About EnCharge AI

## Company Overview
- **One-liner**: EnCharge AI develops analog in-memory computing hardware and software to deliver high-efficiency, low-cost AI inference from edge devices to cloud data centers.
- **Entity Type**: Private (Series B – II stage)
- **Headquarters**: Santa Clara, California, United States
- **Founded**: 2022
- **Founders**: Naveen Verma, Ph.D. (CEO) and Kailash Gopalakrishnan, Ph.D. (CTO)

## Core Business
- **Primary industry**: AI semiconductor hardware and embedded software products
- **Target customers**: B2B – enterprises deploying AI at scale, edge-device manufacturers, cloud service providers, and defense/industrial sectors
- **Mission**: Democratize advanced AI by enabling deployment beyond cloud infrastructure to local servers and mobile devices, while slashing costs and environmental impact

## Products & Services
- **Analog In-Memory Computing GPUs & Digital AI Accelerators**: Custom silicon (chiplets, ASICs) and standard-form-factor PCIe cards that perform AI inference using analog computation for orders-of-magnitude better energy efficiency and compute density.
- **Software Stack**: Seamless orchestration layer that supports on-device and cloud deployment, enabling model portability, quantization, and compiler optimizations across EnCharge’s hardware.
- **Edge-to-Cloud Platforms**: Integrated solutions for power-, space-, and cost-constrained environments, covering autonomous systems, smart devices, data center inference, and private on-premise AI.

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed
- **Key Metrics**: Annual Revenue ~$10M (LinkedIn estimate) | Total Funding $162.9M
- **Notable Investors & Partners**: Tiger Global Management (led $100M Series B, Mar 2025), Anzu Partners (led $21.7M Series A, Dec 2022), DARPA ($18.6M grant, Mar 2024), and others including corporate/institutional backers.
- **Growth Signals**: 
  - 58.6% YoY headcount growth (75 employees, as of mid-2025)
  - 39 active job openings spanning hardware, compiler, and AI architecture roles
  - 150+ patents granted, 300+ technical publications
  - Talent inflows from Intel, IBM, Cerebras, AMD, Meta, Microsoft

## Competitive Advantages
- **Analog In-Memory Computing Moa**t: A proprietary compute architecture that uses charge-domain analog circuits, validated silicon, and leverages existing semiconductor supply chains.
- **Record Efficiency**: Claims 20× higher TOPS/W, 9× higher compute density (TOPS/mm²), 10× lower total cost of ownership, and 100× lower CO₂ emissions compared to leading cloud/GPU alternatives.
- **Deep IP Portfolio**: 150+ granted patents and 300+ publications from 20+ years of foundational research by the founding team (Princeton, IBM, etc.).
- **End-to-End Solution**: Full-stack hardware and software (compiler, quantization, runtime) designed for seamless edge-to-cloud orchestration without vendor lock-in.

## Strategic Focus
- Scale production and customer deployments of their analog in-memory compute chips for high-volume edge and data center inference.
- Expand software ecosystem to support mainstream AI frameworks (PyTorch, TensorFlow, ONNX) and enable easy drop-in replacement for existing GPU-accelerated workloads.
- Deepen partnerships with defense (DARPA) and enterprise cloud providers, emphasizing data privacy, security, and sustainability.
- Double down on sustainability messaging (100× lower CO₂) to meet ESG mandates in enterprise AI procurement.

## Why Work Here
- **Mission-Driven Impact**: Opportunity to make AI accessible to the “99%” by dramatically reducing energy and cost barriers. Work is cited as a “once-in-a-lifetime” chance by leadership.
- **World-Class Team**: Colleagues include industry luminaries from Princeton, IBM, and top semiconductor houses; 57% of staff are in technical roles (engineering, research, compiler).
- **Culture of Collaboration & Innovation**: The careers page highlights integrity, growth, and collaborative problem-solving in a fast-paced startup environment.
- **Comprehensive Rewards**: Benefits package includes typical startup perks; equity likely offered given funding stage.
- **Work Policy**: Hybrid presence indicated by offices in Santa Clara, Canada, Germany, Norway, South Korea, and India. Remote flexibility likely for some roles.
- **Active Hiring**: 39 open positions across DFT, physical design, compiler engineering, and NPU architecture – strong signal of scaling and technical investment.

## Sources
1. [EnCharge AI Official Website](https://www.enchargeai.com/)
2. [EnCharge AI Careers Page](https://www.enchargeai.com/careers)
3. [EnCharge AI About Us (Leadership & Founders)](https://www.enchargeai.com/about-us)
4. [EnCharge AI LinkedIn Company Page](https://www.linkedin.com/company/encharge-ai)
5. [CB Insights Profile – EnCharge AI](https://www.cbinsights.com/company/encharge-ai)

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