ML Ops Lead: GenAI Deployment & FinOps Platform Architect

Anaplan; City Of London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Anaplan in City of London is seeking an ML Ops Technical Lead to spearhead infrastructure, cost-optimisation, and deployment strategies. You will manage a talented DevOps team while remaining deeply technical and hands-on.

Your mission is to build, scale, and secure foundational platforms for ML and GenAI models with financial accountability. Your impact includes leading DevOps, defining infra roadmaps, maintaining MLOps/LLMOps pipelines, production deployment of LLMs, FinOps governance,

Qualifications

• Extensive production experience deploying and supporting ML systems.
• Proven track record leading engineering teams.
• Experience with Generative AI and LLM deployments.
• Strong automation and IaC background.

Responsibilities

• Lead and mentor a DevOps team.
• Define infra roadmap for AI/ML workloads.
• Architect and maintain MLOps pipelines and CI/CD.
• Deploy LLMs to production with high availability.
• Establish FinOps for AI infra spend.
• Implement auto-scaling and cost-controls.
• Establish 24/7 observability and incident response.
• Ensure data governance and platform security.

Skills

ML model deployment

Team leadership

GenAI/LLMOps

Cloud cost optimization

CI/CD for ML

Python/Bash/Go

Kubernetes & Docker

Data governance & security

Observability & incident response

Tools

MLflow

Kubeflow

LangSmith

Phoenix

Kubecost

Cloudability

Terraform

Ansible

Jenkins

GitHub Actions

Kubernetes

Docker

Triton Inference Server

vLLM

Hugging Face TGI

Job description

Anaplan in City of London is seeking an ML Ops Technical Lead to spearhead infrastructure, cost-optimisation, and deployment strategies. You will manage a talented DevOps team while remaining deeply technical and hands-on.

Your mission is to build, scale, and secure foundational platforms for ML and GenAI models with financial accountability. Your impact includes leading DevOps, defining infra roadmaps, maintaining MLOps/LLMOps pipelines, production deployment of LLMs, FinOps governance,