Remote Lead AI Platform Engineer - LLM/MLOps

Oliver James Group; United States; Remote; USD 165,312,000 - 275,520,000; Full time

Job summary

Oliver James Group seeks a hands-on Lead AI Platform Engineer to build and operate production-grade AI infrastructure in AWS, focusing on LLMOps and MLOps. This is a remote, six-month contract with potential for full-time conversion.

You will design CI/CD pipelines, IaC, automation and monitoring; develop LLMOps capabilities including deployment, prompts, evaluation, observability and guardrails; manage model lifecycle, drift detection and retraining.

Qualifications

• Hands-on experience building production AI/ML infrastructure.
• Strong DevOps/SRE background.
• Experience with LLMOps/MLOps in production environments.
• Experience with CI/CD, IaC, automation, observability and production support.
• Understanding of enterprise AI security and governance.

Responsibilities

• Build and operate production AI/ML infrastructure in AWS.
• Design and maintain CI/CD pipelines, IaC, automation and monitoring.
• Develop LLMOps capabilities: deployment, prompt/version management, evaluation, observability and guardrails.
• Manage MLOps: model lifecycle, deployment, monitoring, drift detection and retraining.
• Establish repeatable deployment and promotion processes across dev/test/prod.
• Optimise AI workloads for latency, scalability, reliability, token consumption and cost.
• Implement security, access controls, data protection and governance.
• Build reusable platform capabilities for application teams to integrate AI without managing underlying infra.

Skills

LLMOps

MLOps

DevOps

SRE

AWS

CI/CD

IaC

Observability

Security governance

Tools

AWS

Terraform

Job description

Oliver James Group seeks a hands-on Lead AI Platform Engineer to build and operate production-grade AI infrastructure in AWS, focusing on LLMOps and MLOps. This is a remote, six-month contract with potential for full-time conversion.

You will design CI/CD pipelines, IaC, automation and monitoring; develop LLMOps capabilities including deployment, prompts, evaluation, observability and guardrails; manage model lifecycle, drift detection and retraining.