Senior Software Engineer – NIC & RDMA Driver (Next-Gen AI SmartNIC)

Location: Bangalore [Flexible]

Experience: 12 to 18 Years Exp

Type: Full-time

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About Us

We’re building the next generation of AI SmartNICs — intelligent network accelerators designed to power distributed AI training, data center virtualization, and hyperscale cloud workloads.

Our mission: push networking performance to the limits — from microsecond-level latency to terabit-scale throughput — while giving developers full programmability across compute, network, and storage fabrics. If you love working close to the metal and want to shape the future of data-driven infrastructure, you’ll fit right in.

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What You’ll Do

• Own and build NIC and RDMA kernel drivers for our SmartNIC platform (Linux).
• Design and implement high-performance Tx/Rx and RDMA data paths — QPs, CQs, doorbells, DMA, and WQEs.
• Bring up new silicon: work directly with hardware and firmware teams to validate PCIe, queue interfaces, and offload engines.
• Add networking offloads (TSO, checksum, RSS, VLAN, tunneling: VXLAN/Geneve/GRE).
• Integrate RoCEv2 and user-space RDMA (libibverbs/rdma-core) for AI and storage workloads.
• Build tools for performance measurement, kernel tracing, and packet analytics.
• Collaborate across firmware, DPDK, and P4/eBPF pipeline teams to build a unified data path.
• Push upstream when possible — we’re believers in open standards and open source.

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What You’ll Bring

• 12+ years of Linux kernel or driver development experience (preferably network or RDMA subsystems).
• Strong in C programming, concurrency, and debugging at the kernel level.
• Solid understanding of:

NIC architecture — Tx/Rx rings, CQEs, doorbells, DMA engines.

RDMA fundamentals — QPs, PDs, MRs, WQEs, CQ handling.

PCIe, MMIO, and DMA interactions.

• Experience with rdma-core, DPDK, or low-latency networking stacks.
• Familiarity with SR-IOV, VFIO, and virtio.
• Passion for performance tuning and squeezing out every nanosecond.

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Bonus Points

• You’ve worked with SmartNICs or DPUs (NVIDIA BlueField, Pensando, Broadcom Stingray, Marvell Octeon, etc.).

• You understand how AI/ML training clusters use RDMA for scale-out.

• Experience with eBPF/XDP, P4, or programmable data planes.

• You’ve contributed to Linux netdev or RDMA subsystems.

• You enjoy profiling, tracing, and reverse-engineering hardware behavior.