Remote AI Operations Engineer: MLOps/LLMOps/AgentOps

FinOps Weekly; Northern (KY); Hybrid; USD 120,000 - 160,000; Full time

Job summary

FinOps Weekly is seeking an experienced MLOps/AIOps/LLMOps/AgentOps Engineer to design, operate, and evolve our AI platforms in production across AWS and Azure environments.

You will focus on platform reliability, automation, observability, and scalable pipelines, collaborating with data scientists and engineers to productionize AI solutions. Fluency in English and strong cloud/DevOps skills are essential.

Qualifications

• Hands-on experience in MLOps, AIOps, or operating ML systems in production.
• Strong knowledge of LLMOps and AgentOps concepts (RAGs, agents, evaluation, monitoring).
• Experience with AWS and/or Azure in production environments.
• Experience with containers and Kubernetes (Docker, Helm).
• Experience with CI/CD pipelines (GitHub Actions, GitLab CI, Azure DevOps, Jenkins).
• Familiarity with observability and monitoring concepts (CloudWatch, OpenTelemetry, Prometheus).
• Experience managing infrastructure as code (Terraform, Bicep, CDK, or similar).
• Python and ML ecosystem (scikit-learn, PyTorch).

Responsibilities

• Design, maintain, and evolve the AIOps platform supporting: traditional ML models in production.
• Develop and operate ML and LLM pipelines with focus on reliability and observability.
• Implement cost control and optimization for AI workloads.
• Collaborate with Data Scientists/Engineers to productionize AI solutions.

Skills

MLOps

AIOps

LLMOps

AgentOps

AWS

Azure

Kubernetes

Docker

CI/CD

Observability

IaC

Python

ML lifecycle

English

Tools

Docker

Kubernetes

Terraform

CloudFormation

Bicep

CDK

GitHub Actions

GitLab CI

Azure DevOps

Helm

Job description

FinOps Weekly is seeking an experienced MLOps/AIOps/LLMOps/AgentOps Engineer to design, operate, and evolve our AI platforms in production across AWS and Azure environments.

You will focus on platform reliability, automation, observability, and scalable pipelines, collaborating with data scientists and engineers to productionize AI solutions. Fluency in English and strong cloud/DevOps skills are essential.