Job description

Software Engineer - DevOps, Platform Engineering & Infrastructure Automation You will be part of a high-impact team delivering AI/ML capabilities to end users by building reliable and scalable infrastructure. Your role involves deploying containerized services using Kubernetes and implementing comprehensive observability solutions. You will work closely with data scientists and system administrators to ensure the continuous availability of mission-critical services. Responsibilities: • Deploy and manage containerized AI/ML services using Kubernetes in on-premises environments. • Implement observability and monitoring solutions using Prometheus, Grafana, and related tooling. Required Skills: • Experience deploying and managing services in on-premises infrastructure environments. • Service containerization and orchestration with Docker/Kubernetes in production environments. • Experience with observability and monitoring tools such as Prometheus, Grafana, or equivalent platforms. Nice to Have: • Knowledge of AI infrastructure tools and frameworks (LiteLLM, Bifrost, Ray, Ollama). • Awareness of the current AI/ML landscape including emerging models and applicability to different use cases. Experience Required: 12 years with Bachelor's degree in technical field or 16 years without degree Location: Columbia, MD Clearance: TS/SCI with Polygraph required Salary Range: $204,000 - $247,000

Requirements

Must-haves

Software Engineer - DevOps, Platform Engineering & Infrastructure Automation
Deploy and manage containerized AI/ML services using Kubernetes in on-premises environments.
Implement observability and monitoring solutions using Prometheus, Grafana, and related tooling.
Experience deploying and managing services in on-premises infrastructure environments.
Service containerization and orchestration with Docker/Kubernetes in production environments.
Experience with observability and monitoring tools such as Prometheus, Grafana, or equivalent platforms.
Experience Required: 12 years with Bachelor's degree in technical field or 16 years without degree
Clearance: TS/SCI with Polygraph required

Nice-to-haves

Knowledge of AI infrastructure tools and frameworks (LiteLLM, Bifrost, Ray, Ollama).
Awareness of the current AI/ML landscape including emerging models and applicability to different use cases.
Location: Columbia, MD

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlkubernetesdocker

Platform: neural-solutions
Effort: medium