Hardware Systems Engineer Jobs

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:

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. Physical Design Engineer (2-4 Years Experience) We are looking for a high-caliber Physical Design Engineer to join our fast-paced startup team. This role is designed for "top 1%" talent—engineers from tier-1 universities (IIT/NIT/BITS or equivalent) who possess a relentless "go-getter" attitude and the critical thinking skills required to solve complex, next-generation silicon challenges. If you are eager to move beyond standard digital flows into the future of AI-driven automation , this is your playground. Key Responsibilities End-to-End Ownership: Drive RTL-to-GDSII implementation, including floorplanning, placement, CTS, routing, and physical verification (LVS/DRC/ERC). Performance Optimization: Execute high-performance design closure focusing on PPA (Power, Performance, Area) targets in advanced process nodes ( 3nm or below) Static Timing Analysis (STA): Perform comprehensive timing closure, including signal integrity, crosstalk analysis, and CPPR (Common Path Pessimism Removal) optimization. Power Integrity: Conduct IR-drop analysis (Static/Dynamic) and EM (Electromigration) checks to ensure robust power delivery. Innovation: Develop and integrate AI/ML-based automation scripts to optimize the physical design flow and reduce turnaround time. Qualifications &am

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. Job Description : Lead DFT Engineer (Edge Computing) 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) 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. Tools: Mastery of industry-standard

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. About the Role EnCharge AI is looking for a highly motivated and experienced Staff Physical Design Engineer to drive the physical implementation of our next-generation semiconductor chips. In this role, you will play a critical part in translating complex microarchitectures into high-performance, power-efficient silicon. Working closely with cross-functional teams, you will own block-level and top-level implementation using industry-standard EDA tools, tackle complex timing closure and power challenges, and guide designs all the way from netlist to successful foundry tapeout. Key Responsibilities Drive block-level and top-level physical design, including floor-planning, placement, clock tree synthesis (CTS), and routing. Achieve aggressive timing, power, and area (PPA) targets through advanced timing closure techniques. Perform power grid verification and manage electromigration and IR drop (EM/IR) analysis and resolution. Develop and maintain automation scripts (Tcl/Python) to streamline design flows and methodologies. Collaborate with physical verification and foundry teams to ensure design rule compliance and successful tapeout execution. Qualifications and Requirements Bachelor's or Master’s degree in Electrical Engineering, Computer Engineering, or a related field. 10–15 years of dedicated experience in physical design. Strong understanding of EDA implementation flows

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. Staff Engineer: STA Methodology & Sign-off Lead We are seeking a high-caliber Staff or Senior Staff Engineer to architect and lead our SOC Static Timing Analysis (STA) Methodology along with execution responsibilities to eliminate the bottle-necks in STA and build bridges. This is a critical role for a forward-thinking engineer who excels at defining the frameworks and flows required to navigate the complexities of modern, large-scale SOC designs. Engineer will have scope to bridge Architecture, CAD, RTL, and Physical Design to establish a predictable, high-performance, and scalable path to tape-out. The Role As the lead for STA Methodology, you will own the sign-off architecture and the timing convergence strategy. Rather than just executing runs, you will build the "engine" that enables execution—defining flows, qualifying tools, establishing margin strategies (AOCV/LVF/POCV), and driving cross-functional alignment to meet aggressive Power, Performance, and Area (PPA) targets. Key Responsibilities Sign-off Methodology & Architecture: Define and own full-chip SOC timing sign-off criteria, including Multi-Mode Multi-Corner (MMMC) definitions, derate strategies, and operating condition mapping for functional, shift, and capture modes. Flow Development & Left-Shift Automation: Architect, deploy, and maintain adva

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. Job Title: Senior Physical Design Engineer Experience: 4–7 Years Focus: Block-Level RTL-to-GDSII & PPA Optimization Location: Bangalore Hybrid The Role We are looking for a high-energy, technically curious Physical Design Engineer to join our advanced silicon team. This isn't a role for someone who wants to just "push buttons" on a vendor flow. We need a driver—someone with 4–6 years of experience who has lived through the trenches of quality tape-outs and is hungry to take full ownership of complex partitions. You will be expected to work with a high degree of independence, using your analytical skills to bridge the gap between a standard recipe and a world-class PPA result . You should be comfortable following expert lead direction while maintaining the "question the status-quo" mindset when you see a more efficient path. Key Responsibilities Partition Ownership: Lead the physical implementation of complex blocks from Synthesis and Floor-planning through to CTS, Routing, and Sign-off. PPA Recipe Development: Don't just run the flow—optimize it. You will perform deep-dive analysis on timing paths, power profiles, and congestion to derive custom optimization strategies. Automation-First Mindset: Use Tcl and Python to automate repetitive tasks, build custom analysis scripts, and enhan

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. Job Title: Principal Physical Design Engineer (RTL-to-GDSII) Experience: 14+ Years Technology Focus: Sub-5nm (3nm/2nm) Location: Bangalore Hybrid The Vision We are seeking a Principal Physical Design Engineer who thrives on complexity and rejects the "black box" approach to EDA tools. This role is for a First Principles thinker who questions the status quo. If a standard flow isn't yielding the desired PPA (Power, Performance, Area), you dive into the PDK, the tool algorithms, and the methodology to find a better way. You are responsible for transforming raw RTL into world-class silicon by eliminating systemic bottlenecks and building a scalable, predictable path to GDSII. Key Responsibilities Full-Flow Ownership: Lead the implementation of massive, high-speed blocks/SoCs from Synthesis through Sign-off using the Cadence Digital Suite . PPA Optimization: Push the theoretical limits of the PDK and tools. You will analyze and optimize the interplay between library cells, metal stacks, and tool engines to squeeze out every millivolt and picosecond. Methodology & Scalability: Build and refine a "Push-Button" style execution methodology that is robust, repeatable, and minimizes manual "human-in-the-loop" iterations. Cross-Functional "Left-Shift": Collaborate with RTL, Architecture, and DFT te

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. We are an ambitious AI hardware startup building next-generation accelerators with massive compute density. To achieve aggressive Power, Performance, and Area (PPA) targets on accelerated tapeout schedules, we require a robust, highly automated, and heavily optimized physical implementation and signoff flow. The Role As a Staff / Senior Staff CAD & Methodology Engineer, you will be the resident expert in Innovus and Tempus, responsible for developing, debugging, and continually accelerating our RTL-to-GDSII and timing signoff flows. You will work closely with Physical Design and STA leads to eliminate bottlenecks, automate manual tasks, and push the limits of EDA capabilities at advanced process nodes. Key Responsibilities Flow Architecture & Automation: Architect, develop, and maintain a highly automated, robust, and scalable physical design and signoff flow from synthesis through GDSII, optimized for AI accelerator architectures. Innovus Methodology: Drive advanced physical design methodologies in Cadence Innovus. Optimize recipes for floorplanning, placement, Clock Tree Synthesis (CTS), routing, and power grid implementation to squeeze out maximum PPA. Tempus Signoff Integration: Own the STA and timing signoff methodology using Cadence Tempus. Implement and optimize Distributed Multi-Scenario Analysis (DMSA), advanced OCV methodologies, and automat

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. Job Title: Staff/ Senior Staff Physical Design Engineer (Technical Lead) Experience: Staff 8-10 years Senior Staff 11-13 years Location: Bangalore Hybrid/Remote or Remote in India The Role We are seeking a high-impact Staff/ Senior Staff Physical Design Engineer to serve as a Technical Lead for our next-generation silicon products. This is a "player-coach" role designed for a versatile expert who is equally comfortable architecting a convergence strategy as they are mentoring a small team of engineers. You will own the physical delivery of a major sub-chip or complex block, pushing the absolute limits of PPA (Power, Performance, Area) . As a Staff/Senior Staff lead, you are expected to be the "anchor" of the project—assertive in your decision-making, highly analytical in your debugging, and adept at managing stakeholders to ensure we hit our tape-out milestones without compromise. Key Responsibilities Technical Leadership: Lead a small team of PD engineers, providing technical direction, workload management, and architectural oversight for a sub-chip or partition. SOC clocking , FEV/VCLP specialized skills are preferred. Complex Block/Sub-chip Ownership: Take personal hands-on ownership of the most critical, high-congestion, or timing-critical blocks in the desi

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. About the Role EnCharge AI is looking for a highly experienced, hands-on Principal Solutions Engineer to lead customer and partner solution development, architecture, and deployment for our next-generation AI acceleration platform. This is a senior technical leadership role that combines customer-facing engagement, solution architecture, AI software optimization, and technical mentorship. This role will partner with strategic customers throughout their development lifecycle—from initial technical discovery, architectural evaluation, and proof-of-concepts through production deployment and scaling. Bridging the gap between AI hardware, software, systems, and customers, helping them successfully build, optimize, and scale cutting-edge AI workloads and agentic workflows on EnCharge technology. Serving as the voice of the customer, directly influencing product roadmaps, software features, and developer experience. Responsibilities Serve as the primary technical interface and trusted advisor for strategic customers and partners evaluating and deploying AI workloads on EnCharge platforms. Lead end-to-end customer engagements from technical discovery through proof-of-concept (PoC), design-in, performance benchmarking, system-level tuning, and production deployment. Support technical pre-sales efforts by clearly articulating solution value propositions, architectural differentiator

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. About the Role EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge’s Inference Accelerators. Responsibilities Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization. Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges. Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations. Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR). Implement parsing, semantic analysis, and IR generation for deep learning frameworks. Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers. Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations. Qual

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 emula

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. About the Role EnCharge AI is seeking a highly skilled Device Driver Engineer to design and implement high-performance driver stack for our cutting-edge AI accelerator hardware. In this role, you will work closely with hardware, firmware, and AI software teams to develop low-latency, high-bandwidth communication between the host system and AI accelerator. Responsibilities Develop, optimize, and maintain Linux/Windows PCIe device drivers for AI accelerators. Implement low-level hardware interactions, DMA, memory management, and interrupt handling. Work on driver optimizations to reduce latency and improve throughput for AI workloads. Debug and troubleshoot PCIe protocol, kernel panics, crashes, and performance bottlenecks. Collaborate with hardware, firmware, and AI software teams to define driver interfaces. Ensure compliance with PCIe standards (Gen4/Gen5), SR-IOV, BAR memory mapping, and IOMMU. Support virtualization (VFIO, SR-IOV, DPUs) and containerized environments (Kubernetes, Docker, etc.). Develop tools for profiling, debugging, and monitoring driver performance. Contribute to open-source kernel modules if applicable. Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 3+ years of experience in device driver development for Linux and/or Windows. Strong experience with PCIe-based hardware, including BAR

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. About the Role EnCharge AI is looking for an Embedded SW Engineer to develop the firmware for our Edge AI processors. The candidate must possess an excellent understanding of computer architecture and operating system concepts including, but not limited to, memory management, virtualization and PCIe address space. The role includes designing and developing the core Firmware for various parts of the SOC. The candidate must possess strong communication skills to interface with Runtime, Architecture and H/W teams. Responsibilities Develop the critical pieces of EAI Firmware used to deploy inference jobs on EAI processors Validate different IP blocks on the SOC Evaluate and integrate third-party device drivers to interface with EnCharge’s SW stack Work closely with the Runtime, Hardware and Architecture teams define the driver architecture Qualifications Bachelors in EE/CS Advanced programming skills in C/C++ for operating system kernel & systems development Understanding of RISC-V architecture is a plus Exposure to PCIe BAR and IOMMU architecture Exposure to virtualization and hypervisor technologies Deep understanding of operating systems concepts, data structures, x86-64 and accelerator architectures Experience with low-level debug tools as well as emulators and simulators Experience running, analyzing, and tuning system performance benchmarks Excellent verb

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. About the Role EnCharge AI is seeking an AI Runtime Engineer to develop and optimize the execution stack for our next-generation AI accelerator. In this role, you will work on low-latency, high-performance runtime software that enables efficient execution of deep learning models on specialized hardware. You will collaborate with hardware, compiler, and AI framework teams to deliver optimized AI inference and training performance across cloud and edge environments. Responsibilities Develop and optimize the AI runtime software stack for executing deep learning workloads on AI accelerators. Implement task scheduling, memory management, and kernel execution strategies for efficient computation. Optimize data movement between host and device using PCIe, DMA, shared memory. Design and implement high-performance APIs for AI Inference frameworks such as OpenVino, ONNX Runtime, vLLM Work on graph execution optimizations, including kernel fusion, pipelining, tensor tiling, and caching. Integrate runtime components with AI compilers (LLVM, MLIR, XLA, TVM) for optimized execution. Ensure scalability and reliability of the AI runtime for cloud-based and edge AI deployments. Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 3+ years of experience in developing low-level runtime software for AI accelerators, GPUs, or