Principal Signal Integrity Engineer Location: Greater Bengaluru Area (Hybrid)/ Greater Hyderabad

we are redefining the economics of AI infrastructure. Our mission is to democratise AI by significantly reducing the Total Cost of Ownership (TCO) of hardware systems — a critical barrier to scalable adoption.

Our proprietary MIMO-over-copper technology powers a high-performance, chiplet-based AI memory fabric that is both scalable and energy-efficient. Unlike traditional interconnects, our solution reduces power consumption significantly while preserving high bandwidth and ultra-low latency — unlocking unprecedented efficiency for AI training and inference at scale.

our architecture is not just an incremental improvement — it’s a foundational shift in how AI hardware is built for the future.

. Required Experience:

~10+ years of experience in the semiconductor industry, with a focus on topics related to signal and power integrity

~ Robust foundation in electromagnetics and system-level design, including material (package, PCB, board, connector, cable), as well as analog, power,



and digital electronics

~ Proven leadership of SI/PI, package, and PCB teams delivering multi-Gbps link solutions. Must be able to articulate one or more significant SI problems that were solved with innovative design of connector, package or cable.

~ Work closely with circuit designers to ensure robust SI/PI implementation in silicon

Engage with customers and suppliers to define and validate hardware solutions (packages, PCB/backplane layouts, materials, interposers, connectors) for our products

Perform and lead theoretical and simulation-based SI analysis of products, channels, test structures, and system implementations

Chord signaling, PAM) in terms of SI/PI performance, power, and implementation trade-offs

Experience with channel modeling and extraction for multi-Gbps systems, including end-to-end link considerations

Proficiency in Linux-based design environments and scripting (M

📌 Engineer (Hyderabad)
🏢 Kandou AI
📍 Hyderabad