Staff Observability Engineer

Remote

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Semiconductors, Cloud ComputingIndustries

Requirements

Candidates should possess 4+ years of experience in observability as a core responsibility of previous roles, a deep understanding of cloud-native technologies and infrastructure as a service (IaaS) such as Terraform and Flux, expertise in standing up and running monitoring, observability, and alerting systems - OpenTelemetry Tracing and Collector, Grafana/Prometheus, PagerDuty, AlertManager, IPMI, SNMP, and familiarity with and strong opinions on signals including effective canonical logging and cost control, tracing expertise including context propagation, tail sampling strategies, attribute enrichment, querying, and metrics derived from a variety of systems such as hosts, kube-state-metrics, kubelet, IPMI, SNMP. Experience instrumenting large Kubernetes clusters and building operators is also required.

Responsibilities

The Staff Observability Engineer will build and maintain comprehensive observability systems at massive scale, constantly iterating on, maintaining, updating, and automating their own systems, and putting in place great monitoring of their own systems that can be used as best practices by the rest of the organization. They will instrument Kubernetes clusters, applications, and datacenter infrastructure components such as switches, PDUs, environmental sensors, cameras, chillers, etc. Additionally, they will be a teacher, advising teams on instrumenting their applications in various languages (Rust, C++, TypeScript, GoLang), implementing sensible SLO and alerting strategies, and on-call best practices.

Skills

Kubernetes

Tracing

Logging

Metrics

Instrumentation

Monitoring

Automation

Observability

Datacenter Infrastructure

Networking

Alerting

Debugging

SLOs

On-call

Groq

AI inference technology for scalable solutions

About Groq

Groq specializes in AI inference technology, providing the Groq LPU™, which is known for its high compute speed, quality, and energy efficiency. The Groq LPU™ is designed to handle AI processing tasks quickly and effectively, making it suitable for both cloud and on-premises applications. Unlike many competitors, Groq's products are designed, fabricated, and assembled in North America, which helps maintain high standards of quality and performance. The company targets a variety of clients across different industries that require fast and efficient AI processing capabilities. Groq's goal is to deliver scalable AI inference solutions that meet the growing demands for rapid data processing in the AI and machine learning market.

Mountain View, CaliforniaHeadquarters

2016Year Founded

$1,266.5MTotal Funding

SERIES_DCompany Stage

AI & Machine LearningIndustries

201-500Employees

Benefits

Remote Work Options

Company Equity

Risks

Increased competition from SambaNova Systems and Gradio in high-speed AI inference.

Geopolitical risks in the MENA region may affect the Saudi Arabia data center project.

Rapid expansion could strain Groq's operational capabilities and supply chain.

Differentiation

Groq's LPU offers exceptional compute speed and energy efficiency for AI inference.

The company's products are designed and assembled in North America, ensuring high quality.

Groq emphasizes deterministic performance, providing predictable outcomes in AI computations.

Upsides

Groq secured $640M in Series D funding, boosting its expansion capabilities.

Partnership with Aramco Digital aims to build the world's largest inferencing data center.

Integration with Touchcast's Cognitive Caching enhances Groq's hardware for hyper-speed inference.

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