
EnCharge AI provides efficient, low‑power AI computing solutions that let businesses run advanced models from edge devices to the cloud. The company designs analog in‑memory computing chips and pairs…

EnCharge AI provides efficient, low‑power AI computing solutions that let businesses run advanced models from edge devices to the cloud. The company designs analog in‑memory computing chips and pairs…
Founded: 2022 (Princeton University spinout)
Headquarters: Santa Clara (evidence: company described as Santa Clara–based)
Product: Analog in-memory AI accelerators with hardware/software stack for edge-to-cloud
Recent funding: Series B (Feb 13, 2025) > $100M led by Tiger Global
Total funding reported: $162.9M (currency: USD)
Energy-efficient AI inference for edge and cloud (power-constrained applications, on-device/edge deployments).
2022
Data and Analytics
21700000
Reported $21.7M; participants included AlleyCorp, Scout Ventures, Silicon Catalyst Angels and others.
22600000
Reported $22.6M round (brought total to ~$45M at that time); participants included VentureTech Alliance, RTX Ventures, ACVC Partners, Anzu Partners, S5V, AlleyCorp, Scout and Silicon Catalyst Angels.
100000000
Reported as more than $100M Series B led by Tiger Global.
“Includes strategic and financial investors such as Tiger Global, VentureTech Alliance (TSMC-related), RTX Ventures, Samsung Ventures and a mix of VC and corporate backers”
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(www.enchargeai.com)
Senior Staff DFT Engineer
Location: Greater Bengaluru Area (Hybrid-2 days office,3 days-home) or Remote (any where in India
About Company:
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.
Developing silicon for Edge 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) Senior staff, 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, 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 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.
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: 10-14 years in DFT, with at least 2 years in a leadership or principal role.
Tools: Mastery of industry-standard tools (e.g., Synopsys TestMAX, Siemens/Mentor Tessent, or Cadence Modus).
Memory & Logic Test: Deep expertise in MBIST (Memory Built-In Self-Test) with repair capabilities 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.
Contact
Uday
muday_bhaskar@yahoo.com
Mulya Technologies
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