--- title: 'Lead DFT Engineer at EnCharge AI' canonical: 'https://feeny.ai/job/lead-dft-engineer-encharge-ai-canada-united-states-q4ggksnf4q7g' type: 'job' last_seen: '2026-09-12' --- # Lead DFT Engineer at EnCharge AI - **Company:** EnCharge AI - **Location:** Canada / United States - **Work type:** remote - **Posted:** 2026-08-13 - **Last confirmed live:** 2026-09-12 - **Apply:** https://job-boards.greenhouse.io/enchargeai36/jobs/4369637009 ## 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. Lead DFT Engineer Job Description: Developing silicon for edge-to-cloud computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities: Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory/Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis. Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements: Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Bachelor’s degree in a related field. Tools: Mastery of industry-standard tools (e.g., Synopsys TestMAX, Siemens/Mentor Tessent, Cadence Modus). Memory & Logic Test: Deep expertise in MBIST (Memory Built-In Self-Test) with repair capabilities, SCAN, IJTAG (IEEE 1687) and boundary scan (IEEE 1149.1/6). Advanced Nodes: Proven track record with FinFET nodes (7nm, 5nm, or below). Low Power: Experience managing DFT in multi-voltage/power-gated designs—crucial for edge efficiency. EnCharge AI is an equal employment opportunity employer in the United States. The salary range for this position is $200,000 to $250,000 USD/CAN per year. Actual compensation offered will be determined based on job-related knowledge, skills, and experience. ## 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. 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