Sr./Staff Network Design Engineer, AI/HPC

Groq•New York, NY

7h•$270,400 - $401,600•Hybrid

About The Position

Groq is building high-performance AI infrastructure designed to make inference fast, predictable, and scalable. Our infrastructure teams design and operate the systems that connect compute, data, and services at significant scale. We are looking for a Sr./Staff Network Engineer, AI/HPC to help architect, design, validate, and evolve the network infrastructure supporting Groq's rapidly growing AI compute environments. As a Sr./Staff Network Design Engineer, you will own network architecture and design across high-performance data center and AI infrastructure environments. You will translate capacity, performance, reliability, and business requirements into scalable network designs that can be deployed and operated consistently. This role requires deep expertise in data center networking, routing protocols, network architecture, automation, and large-scale infrastructure. You will work closely with network operations, data center engineering, compute, platform, security, and infrastructure teams to take designs from concept through validation and production deployment. You will also help establish the engineering standards, design patterns, tooling, and technical direction that allow Groq's network infrastructure to scale. In this role, success means building network architectures that allow Groq's infrastructure to grow without sacrificing performance, reliability, or operational simplicity. You will create repeatable designs rather than one-off solutions, automate wherever practical, identify scaling limits before they become production problems, and make the network an enabling layer for Groq's compute infrastructure. You'll combine deep networking expertise with a systems engineering mindset—considering not only whether a network works, but how it behaves at scale, how it fails, how it is validated, and how efficiently it can be operated.

Requirements

8+ years of experience in network engineering, architecture, or infrastructure engineering, with significant experience designing large-scale data center networks.
Deep understanding of TCP/IP, BGP and modern data center routing architectures.
Strong experience designing leaf-spine / Clos network fabrics.
Experience with EVPN/VXLAN and modern network virtualization architectures.
Strong understanding of ECMP, routing convergence, failure domains, traffic engineering, and network resiliency.
Experience designing networks with high-bandwidth Ethernet platforms, including 100G, 400G, or higher-speed interfaces.
Strong knowledge of optical networking fundamentals, transceivers, fiber infrastructure, and data center cabling.
Experience with network platforms and operating systems from vendors such as Arista, Cisco, Juniper, NVIDIA, or equivalent.
Experience with network automation and software development using Python and APIs.
Familiarity with infrastructure-as-code, source control, automated testing, and CI/CD engineering practices.
Experience with network telemetry and observability technologies such as streaming telemetry, SNMP, flow data, and time-series monitoring.
Strong understanding of Linux networking and TCP/IP fundamentals.
Demonstrated ability to develop architecture documents, design standards, implementation plans, and technical specifications.
Ability to analyze complex systems and make sound architectural decisions involving performance, reliability, cost, and operational tradeoffs.
Strong communication skills and the ability to influence technical decisions across engineering organizations.
Experience designing networks for AI/ML clusters, HPC environments, distributed computing systems, or large GPU/accelerator deployments.
Experience with very large-scale Ethernet fabrics and high-throughput east-west traffic patterns.
Knowledge of RDMA, Priority Flow Control (PFC), ECN, congestion management, and lossless or near-lossless Ethernet design.
Familiarity with backend technologies like Infiniband/RoCE/ Spectrum-X experience strongly preferred
Experience designing networks supporting distributed training or large-scale AI inference.
Familiarity with SONiC or other disaggregated/open networking platforms.
Experience with multi-site data center architecture and data center interconnect.
Experience working with cloud networking environments such as AWS, GCP, or Azure.
Familiarity with network source-of-truth and automation platforms such as NetBox, Nautobot, or equivalent systems.
Experience designing and operating infrastructure at hyperscale or in rapidly growing technology environments.

Responsibilities

Own the end-to-end network design process, translating customer compute, workload, scale, and tenancy requirements into production-ready architectures for AI training and inference.
Work closely with software teams building inference and training stacks to align network topology with stack architecture.
Develop network architectures, high-level designs (HLDs), low-level designs (LLDs), review bill of materials (BOMs), and implementation standards leveraging industry and vendor reference architectures.
Design spine-leaf/Clos fabrics across front-end, back-end, and storage networks, with a focus on performance, resiliency, scalability, and operational simplicity.
Evaluate and implement technologies such as BGP, EVPN, VXLAN, ECMP, IPv4/IPv6, QoS.
Develop strategies for data center interconnect, WAN connectivity, internet edge, cloud connectivity, and external peering.
Perform network capacity planning and traffic engineering for high-bandwidth AI and distributed compute workloads.
Partner with compute and infrastructure engineering teams to understand workload communication patterns and translate them into network requirements.
Establish standards for network hardware platforms, topology, addressing, routing policy, configuration, and lifecycle management.
Evaluate switches, optics, cabling architectures, network operating systems, and emerging networking technologies.
Build lab environments, proofs of concept, and design-validation frameworks before introducing new architectures into production.
Define failure scenarios and validate network behavior during link, device, control-plane, and site failures.
Drive network automation and infrastructure-as-code practices using technologies such as Python, Ansible, Git, APIs, and CI/CD pipelines.
Develop automated design validation, configuration generation, compliance, and testing capabilities.
Establish network observability requirements, including telemetry, performance metrics, alerting, and capacity visibility.
Lead technical reviews and provide guidance on complex network architecture and design decisions.
Troubleshoot complex performance and reliability issues that span network, compute, hardware, and distributed systems.
Partner with operations teams to ensure designs are supportable, observable, and safe to operate at scale.
Mentor engineers and raise the technical bar for network architecture, automation, documentation, and engineering practices.