[Hiring] Lead Cloud Infrastructure Engineer / Site Reliability Engineer @Job Board

Role Description

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
• 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.

Qualifications

• 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.

Requirements

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

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.

Benefits

• Compensation Range: $172,000 — $219,000 USD
• Equity and additional benefits will also be awarded.