Staff Observability Engineer

Sorry, this job was removed at 12:11 a.m. (CST) on Thursday, Aug 14, 2025
Easy Apply
4 Locations
In-Office or Remote
Artificial Intelligence • Machine Learning • Semiconductor
The Role

About Groq

Groq delivers fast, efficient AI inference. Our LPU-based system powers GroqCloud™, giving businesses and developers the speed and scale they need. Headquartered in Silicon Valley, we are on a mission to make high performance AI compute more accessible and affordable. When real-time AI is within reach, anything is possible. Build fast.

Staff Observability Engineer

Mission: Ensure the reliability, scalability, and performance of Groq’s observability tools and services for provisioning and managing the full lifecycle of Groq hardware, software, and networking systems at massive scale.

The team: The observability team builds the monitoring and observability infrastructure and tooling that supports Groq’s inferencing hardware at massive scale, both in the cloud and our own datacenters. Our mission is to enable the reliability, scalability, and performance of Groq’s tools and service across a wide range of signals and appliances, to support teams in production excellence, and to evangelize technical and cultural best practices around alerting, instrumentation, debugging, SLOs, and on-call.

Responsibilities & opportunities in this role:

  • Build and maintain comprehensive observability systems at massive scale. Obsess about running high quality production systems with excellent uptime that engineers can trust.
  • Constantly iterate on, maintain, update, automate, and dogfood your own systems. Put in place great monitoring of your own systems that can be used as best practices by the rest of the organization.
  • Instrument Kubernetes clusters, applications, and datacenter infrastructure components such as switches, PDUs, environmental sensors, cameras, chillers, etc.
  • Familiarity with and strong opinions on signals:
    • Effective canonical logging and cost control
    • Tracing expertise including context propagation, tail sampling strategies, attribute enrichment, querying
    • Metrics derived from a variety of systems such as hosts, kube-state-metrics, kubelet, IPMI, SNMP
  • Be a teacher: adviser teams on instrumenting their applications in a variety of languages (Rust, C++, TypeScript, GoLang), implementing sensible SLO and alerting strategies, as well as on-call best practices

Ideal candidates have/are:

  • 4+ years of experience in observability as a core responsibility of previous roles
  • Deep understanding of cloud-native technologies and infrastructure as a service (IaaS) such as Terraform and Flux.
  • Have instrumented large kubernetes clusters and built operators
  • Expertise in standing up and running monitoring, observability, and alerting systems - OpenTelemetry Tracing and Collector, Grafana/Prometheus, PagerDuty, AlertManager, IPMI, SNMP, etc.
  • Strong analytical and problem-solving skills with a focus on root cause analysis and mitigation.
  • Excellent communication and teamwork skills with the ability to collaborate effectively across engineering teams.

Attributes of a Groqster:

  • Humility - Egos are checked at the door
  • Collaborative & Team Savvy - We make up the smartest person in the room, together
  • Growth & Giver Mindset - Learn it all versus know it all, we share knowledge generously
  • Curious & Innovative - Take a creative approach to projects, problems, and design
  • Passion, Grit, & Boldness - no limit thinking, fueling informed risk taking

If this sounds like you, we’d love to hear from you!

Compensation: At Groq, a competitive base salary is part of our comprehensive compensation package, which includes equity and benefits. For this role, the base salary range is $186,915 to $252,885 determined by your skills, qualifications, experience and internal benchmarks.

#LI-Remote

Location: Some roles may require being located near or on our primary sites, as indicated in the job description.  

At Groq: Our goal is to hire and promote an exceptional workforce as diverse as the global populations we serve. Groq is an equal opportunity employer committed to diversity, inclusion, and belonging in all aspects of our organization. We value and celebrate diversity in thought, beliefs, talent, expression, and backgrounds. We know that our individual differences make us better.


Groq is an Equal Opportunity Employer that is committed to inclusion and diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, disability or protected veteran status.  We also take affirmative action to offer employment opportunities to minorities, women, individuals with disabilities, and protected veterans.

Groq is committed to working with qualified individuals with physical or mental disabilities. Applicants who would like to contact us regarding the accessibility of our website or who need special assistance or a reasonable accommodation for any part of the application or hiring process may contact us at:  [email protected].  This contact information is for accommodation requests only.  Evaluation of requests for reasonable accommodations will be determined on a case-by-case basis.

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The Company
HQ: Mountain View, California
205 Employees
Year Founded: 2016

What We Do

Groq is an AI solutions company delivering ultra-low latency AI inference with the world's first Language Processing Unit™. With turnkey generalized software and a deterministic Tensor Streaming architecture, Groq offers a synchronous ecosystem built for ultra-fast inference at scale. Groq solutions maximize human capital and innovative technology performance, having been proven to reduce developer complexity and accelerate time-to-production and ROI. Designed, engineered, and manufactured completely in North America, Groq offers domestically-based and scalable supply that is available now, capable of delivering 390 racks in 6-12 months and ramped lead times of 6-12 weeks. Learn more at groq.com.

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