MLOps​/LLMOps Engineer

Build the infrastructure that keeps ML and LLM systems observable, testable, deployable, and trustworthy.

• Create repeatable paths from experiment to production.
• Improve AI reliability through evaluation, monitoring, and deployment discipline.
• Support teams building models, retrieval systems, and agents.

• Build model deployment, evaluation, prompt/version management, and monitoring workflows.
• Automate CI/CD for AI services and data-dependent applications.
• Implement observability for model quality, cost, latency, drift, and failures.
• Support secure integration with model providers and cloud AI services.

• 4+ years of platform, ML infrastructure, Dev Ops, or backend engineering experience.
• Experience with containers, CI/CD, observability, and production services.
• Familiarity with model deployment, LLM evaluation, or data pipelines.
• U.S. Citizenship is required.
• Must be capable of obtaining and maintaining a Top Secret security clearance.
• Comfort working with ambiguous mission, data, and engineering problems.
• Strong written communication and ability to explain technical decisions to technical and non-technical teams.

• AWS experience is a plus, especially secure cloud, Gov Cloud, serverless, data, or AI services.
• AI, machine learning, LLM, agentic workflow, or decision intelligence experience is a plus.
• Experience in defense, government, manufacturing, aerospace, logistics, or other mission-critical environments is a plus.

Anautics evaluates candidates based on role-relevant skills, judgment, ownership, and ability to work in high-trust environments. AWS and AI experience are strong pluses across this hiring plan.