# Sr./Staff Forward Deployed Engineer at Groq

- Company: Groq
- What the company does: Groq is the premier neocloud for fast inference. One fully integrated platform for infrastructure, inference, and control. Millions of developers run trillions of tokens on Groq every week. Backed by Purple Arch Ventures.
- Company website: https://groq.com
- Type: Startups
- Level: Senior
- Location: New York, United States
- Work setup: On-site
- Pay: $270K to $402K base salary per year (USD)
- Posted: 2026-10-06
- Apply by: 2026-11-20
- Apply: https://jobs.gem.com/groq/am9icG9zdDozN-fV_wbTMo3R7JVnIEOP?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/groq-sr-staff-forward-deployed-engineer-2/

## About the role

As a Sr./Staff Forward Deployed Engineer focused on AI Infrastructure at Groq, you will work at the frontier of large-scale AI systems, taking complex customer infrastructure programs from requirements to working production environments. You’ll help bring some of the newest accelerator and infrastructure technologies into production, spanning next-generation NVIDIA GPU systems alongside Groq’s purpose-built inference platform. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- Own technical execution across complex customer engagements, from discovery and architecture through PoCs, demos, deployment, cluster bring-up, validation, acceptance, production readiness, and operational handoff
- Translate incomplete or ambiguous customer requirements into practical architectures, implementation plans, test criteria, runbooks, and concrete engineering actions
- Work hands-on across Linux, bare-metal infrastructure, Kubernetes and Slurm, networking, storage, observability, automation, and Groq platform integrations to bring customer environments online and resolve issues
- Support large-scale GPU and LPX deployments, including infrastructure bring-up, cluster health and performance validation, workload testing, benchmarking, failure isolation, and production-readiness evidence
- Understand customer AI workloads well enough to reason about training and inference behavior, concurrency, throughput, latency, data movement, caching, scheduling, and infrastructure bottlenecks
- Troubleshoot production and pre-production issues that cross organizational or technical boundaries, drive them to resolution, and coordinate the right internal experts without losing end-to-end ownership


Source: 1752vc Careers, https://www.1752.vc/careers/jobs/groq-sr-staff-forward-deployed-engineer-2/