Corelight

cybersecurity

LeadCloudInfrastructureEngineer/SiteReliabilityEngineer(SRE)

$172–210k North America Region Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Cloud Infrastructure Engineer / Site Reliability Engineer (SRE) at Corelight. Skills: Cloud Infrastructure Engineering, Site Reliability Engineering (SRE), Kubernetes, AI/ML/LLM Infrastructure, Infrastructure as Code (Terraform), Automation (CI/CD, GitOps), Observability (Prometheus, Grafana), FedRAMP Compliance. Ensure stability, performance, and security of Federal region’s cloud platform. Manage infrastructure and operations with a focus on availability, latency, performance optimization”

What You'll Achieve.

ensure the stability, performance, and security of our Federal region’s cloud platform; speed incident response; proactively hunt for threats; meet the highest standards of security and compliance; create an efficient, reliable, and scalable infrastructure; ensure high reliability and performance of AI/ML/LLM infrastructure; streamline ML/LLM tasks across the Large Language Model lifecycle; disrupt cyber attacks

Industry & Context.

cybersecurity
Problems you'll solve

analytical skills; problem-solving

Eligibility Requirements

U. S. citizenship, Residence within the contiguous United States, Willingness to undergo a Single Scope Background Investigation, 24x7 on-call rotations

What They're Looking For.

Must Have

8+ years in SRE, DevOps, Platform Engineering, MLOps, or Cloud Infrastructure roles, 4+ years of production experience with Kubernetes (EKS, GKE, AKS) and containerization tools like Docker, programming skills in Python, proficiency in Zyphyrscript, Bash, Go, or PowerShell, Proficiency with Infrastructure-as-Code tools (Terraform, CloudFormation), Experience with Kubernetes Operators, Helm, GitOps (ArgoCD, Flux), or Service Mesh (Istio, Linkerd), Exposure to serverless compute (AWS Lambda, Azure Functions), Experience building or automating data and model pipelines for AI/ML/LLM workloads (e.g., RAG, fine-tuning, inference), understanding of observability and monitoring using Prometheus, Grafana, ELK/EFK, Langfuse, or similar platforms, Familiarity with SLI/SLO/SLA practices, incident response, and reliability engineering in production environments, U. S. citizenship at the time of hire, Residence within the contiguous United States, Willingness to undergo a Single Scope Background Investigation, if required

Nice to Have

Cloud certifications (AWS, Azure, or GCP – e.g., Solutions Architect, DevOps Engineer), Experience with agentic AI frameworks (CrewAI, LangGraph, AutoGen), Background in hybrid or on-prem AI deployments, including OpenShift or Rancher, Familiarity with configuration management (Ansible, Chef, Puppet), Contributions to open-source AI/ML, DevOps, or platform tooling, Experience with multimodal AI or model observability platforms (RAGAS, AgentOps, Langtrace), Distributed Tracing, OpenTelemetry, Knowledge of performance tuning, cost efficiency, or capacity planning for AI/LLM infrastructure, Understanding of security controls and FedRAMP compliance for cloud and various workloads

What You'll Do.

and security of Federal region’s cloud platform

Manage infrastructure and operations with a focus on availability

performance optimization

and capacity planning

Maintain a FedRAMP-compliant environment

Maintain core infrastructure services that are robust

and capable of processing high volumes of data

and scale AI/ML/LLM infrastructure across cloud platforms (AWS

Manage and optimize Kubernetes environments (EKS

Build and automate end-to-end data and model pipelines for fine-tuning

Utilize automation tools (GitOps

containerization) to streamline ML/LLM tasks

and reliability best practices

Participate in 24x7 on-call rotations

Lead incident response

and cost optimization

Own infrastructure end to end

leading scaling initiatives

How You'll Work.

Team & Collaboration

Collaborate with software engineering teams to ensure the reliability, performance, and security of the Federal region’s infrastructure; Working closely with teams to meet the highest standards of security and compliance; Providing technical leadership across the team

Full Job Description

Do you want to help make the world safe from cyber attack? At Corelight, we believe that the best approach to cybersecurity risk starts with the network. Attackers can evade endpoint detection, firewalls and many other technologies - but they can’t avoid leaving digital footprints on the networks they traverse. Built on open-source innovations from Zeek, Suricata and YARA and refined through years of real-world use, Corelight transforms network footprints from physical, virtual and cloud networks into actionable insights. Our customers use these insights to speed incident response and proactively hunt for threats. As a Lead Cloud Infrastructure Engineer / Site Reliability Engineer (SRE), you will ensure the stability, performance, and security of our Federal region’s cloud platform. You’ll manage infrastructure and operations with a focus on availability, latency, performance optimization, monitoring, incident response, and capacity planning. This role requires maintaining a FedRAMP-compliant environment and working closely with teams to meet the highest standards of security and compliance. We adopt an "everything as code" approach, leveraging automation and best practices to create an efficient, reliable, and scalable infrastructure. You will be instrumental in maintaining core infrastructure services that are robust, secure, and capable of processing high volumes of data seamlessly. The successful candidate must be a U. S. citizen and may need to perform work that the U. S. government has specified can only be carried out by a U. S. citizen on U. S. soil. Responsibilities Collaborate with software engineering teams to ensure the reliability, performance, and security of the Federal region’s infrastructure. Design, deploy, and scale AI/ML/LLM infrastructure across cloud platforms (AWS, Azure, or GCP) ensuring high reliability and performance. Manage and optimize Kubernetes environments (EKS, AKS, GKE) for AI services, data pipelines, and model operations. Build an

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