9 hours ago
Worth, IL, USASenior / Staff+
H1B sponsor
Base Salary
$270k - $402k/yr
Responsibilities
- Own technical execution for customer engagements from discovery and architecture through proofs of concept, deployment, cluster bring-up, validation, production readiness, and operational handoff.
- Translate ambiguous customer requirements into architectures, implementation plans, test criteria, runbooks, and engineering actions.
- Work hands-on across Linux, bare-metal infrastructure, Kubernetes, Slurm, networking, storage, observability, automation, and Groq platform integrations.
- Support GPU and LPX deployments through cluster health validation, workload testing, benchmarking, failure isolation, and production-readiness assessment.
- Reason about AI training and inference workloads, including concurrency, throughput, latency, data movement, caching, scheduling, and infrastructure bottlenecks.
- Lead customer discovery, architecture reviews, demonstrations, proofs of concept, and technical discussions with engineering and business stakeholders.
- Partner with Networking and Security teams on connectivity, routing, load balancing, network policy, access controls, and security architecture requirements.
- Troubleshoot cross-functional production and pre-production issues and drive them through resolution.
- Build reusable automation, tooling, reference architectures, test suites, deployment patterns, documentation, and platform improvements.
- Bring customer feedback and field evidence to Product and Engineering to inform repeatable platform capabilities.
Requirements
- At least 4 years of hands-on experience building, deploying, operating, or troubleshooting cloud infrastructure, AI infrastructure, HPC systems, large-scale platforms, or comparable production environments.
- Strong Linux and distributed-systems fundamentals with practical experience in Kubernetes, Slurm, bare-metal environments, or comparable infrastructure platforms.
- Technical depth in GPU or accelerator systems, networking, storage, orchestration/platform engineering, or infrastructure reliability, with breadth across adjacent layers.
- Working knowledge of AI training and inference workloads and their effects on compute, networking, storage, scheduling, latency, and throughput.
- Strong Python, Go, Bash, or equivalent scripting and programming skills for diagnostics, automation, deployment tooling, testing, or integrations.
- Demonstrated experience personally debugging and delivering systems rather than working only at the architecture, project-management, or escalation level.
- Ability to break ambiguous problems into concrete technical actions and resolve issues spanning multiple teams.
- Strong written and verbal communication skills for requirements gathering, explaining technical tradeoffs, and documenting reproducible work.
- Preferred experience includes neocloud, hyperscaler, AI infrastructure provider, HPC, frontier AI, or large-scale accelerator infrastructure environments.
- Preferred hands-on experience with NVIDIA GPU infrastructure, multi-node GPU clusters, high-performance storage, infrastructure automation, lifecycle tooling, networking, security diligence, technical proofs of concept, benchmarks, and production-readiness criteria.
Benefits
- Total cash compensation is described as level-dependent and includes potential bonus value in base pay; the listed ranges are $270,400-$318,100 for Staff and $341,400-$401,600 for Sr. Staff.
- Groq offers a Long-Term Incentive Program and a robust suite of employee benefits.
- Hiring is prioritized in or near the San Francisco Bay Area, New York City, and Dallas.
- International compensation varies based on local market dynamics, and the listed compensation ranges apply to candidates located in the United States.
Tech Stack
Categories
Forward Deployed
About Groq
Groq designs and operates AI inference hardware and cloud services built around its LPU architecture, aimed at developers and enterprises running large language models and other ML workloads. It generates revenue by selling processors and offering pay-as-you-go inference through its hosted platform and APIs. Founded in 2016 and headquartered in Mountain View, California, the company is privately held.