DevOps Engineer (Vision)
Core
Design, operate, and secure deployment platforms for LLM applications, agentic systems, and RAG pipelines across cloud, on-premises, and air-gapped environments.
Role type
Senior DevOps Engineer (AI/ML Infrastructure)
Builds
Production-grade inference infrastructure, CI/CD pipelines for model delivery, and secure data services for corrections and intelligence missions.
Domain
AI/ML Infrastructure, Government/Defense Compliance (CJIS, FedRAMP)
Deliverable
production ML models | infrastructure
Required skills
Kubernetes, Terraform, Python, GPU infrastructure management, CI/CD, GitOps, IAM, secrets management, observability, compliance frameworks
Preferred skills
vLLM, TGI, Triton, LangSmith, Langfuse, MLflow, vector/graph databases, policy as code, air-gapped deployment patterns
Technologies
Kubernetes, Terraform, Python, Bash, CUDA, Prometheus, Grafana, OpenTelemetry, Datadog, vLLM, Langfuse, MLflow, Neo4J, ArgoCD, Jenkins, AWS, Azure, VMware
Responsibilities
Design and operate deployment platforms for LLM applications and RAG pipelines; Build CI/CD pipelines for model and application delivery; Establish and maintain inference infrastructure including GPU clusters and vector databases; Operate Kubernetes for AI workloads with GPU scheduling; Implement observability for infrastructure and AI-specific metrics; Harden environments to CJIS, FedRAMP, and DoD controls; Manage AI incident response and security compliance.
Seniority
Senior, hands-on IC