Be part of the team that defends the networks the world depends on

Corelight defends the world’s most sensitive networks—from global commerce to national defense—quietly, relentlessly, and with resolve. As cyber threats grow faster and smarter, we serve as the trusted force behind network resilience, putting elite defense within reach.

By transforming digital footprints from physical, virtual, and cloud networks into actionable insights, we empower defenders to illuminate blind spots and stay ahead of an evolving threat landscape. Built on open-source innovations and fueled by industry leading agentic AI technology, Corelight helps teams to detect advanced threats and close cases with unprecedented clarity and precision.

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 and automate end-to-end data and model pipelines for fine-tuning, inference, and RAG workloads using Terraform, Python, and CI/CD tooling.
Utilize automation tools such as GitOps, CI/CD pipelines, and containerization technologies (Docker, Kubernetes) to streamline ML/LLM tasks across the Large Language Model lifecycle.
Implement monitoring, observability, and reliability best practices using Prometheus, Grafana, ELK/EFK, Langfuse, and SLI/SLO/SLA frameworks.
Participate in 24x7 on-call rotations, leading incident response, performance tuning, and cost optimization across SaaS Platform and production workloads
Own infrastructure end to end, leading scaling initiatives, deployments, and automation, and providing technical leadership across the team

Qualifications/Requirements:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent experience.
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.
Strong programming skills in Python and 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).
Strong 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.

Preferred Qualifications (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.

Additional Requirements

Due to the criteria and security levels required for Corelight’s FedRAMP program, this position requires:

U.S. citizenship at the time of hire.
Residence within the contiguous United States.
Willingness to undergo a Single Scope Background Investigation, if required.

Notice of Pay Transparency:
The compensation for this position may vary depending on factors such as your location, skills and experience. Depending on the nature and seniority of the role, a percentage of compensation may come in the form of a commission-based or discretionary bonus. Equity and additional benefits will also be awarded.

Compensation Range

$172,000—$219,000 USD

Why Join Us?

Fueled by investments from top-tier venture capital organizations such as Crowdstrike, Accel and Insight, Corelight is one of the fastest growing network detection and response platforms in the industry. Our passionate team thrives in a collaborative, inclusive, and geographically distributed culture. We embrace diverse perspectives, neurodiversity, curiosity and low ego results - fostering an environment where every innovator can solve the toughest challenges in cybersecurity and contribute their best work.

We are looking forward to meeting you. Check us out at www.corelight.com