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# AI DevOps Engineer

- **Company:** U.S. Bank
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Bash Shell, Continuous Integration, DevOps, Monitoring of Systems, Identity and Access Management, Key Management, PCI Data Security Standards, Systems Development Life Cycle, Role-Based Access Control, Reliability Engineering, Data Logging, Scripting, Large Language Models, Gitlab, Kubernetes, Deployment Automation, Machine Learning Operations, Functional Programming, Cloudwatch, Api Gateway, Terraform, Software Version Control, Docker, Jenkins
- **Published:** July 28, 2026
- **Apply:** https://dejobs.org/x/x/79B138F2232B4B7286FE085376F17A6A/job/

## About the Role

* LLMOps / MLOps - model serving, gateway/proxy management, prompt/version management, guardrails at runtime.
 * Experience hosting AI/agentic platforms as a shared internal service (multi-tenant).
 * Bedrock / model-hosting and API gateway management.
 * FinOps for AI (usage-based cost optimisation).
 * LangGraph, LangChain understanding

## Description

The AI DevOps Engineer owns the deployment, operations, and reliability of the AI-SDLC platform as it transitions from local/team execution to a centralised, hosted enterprise service. This person builds and manages the infrastructure, CI/CD, monitoring, and observability that keep the platform available, secure, and scalable across multiple teams and products. They automate deployments, maintain pipelines, and provide operational support, playing a critical role in productionising the AI-SDLC and ensuring it meets enterprise SLAs, security, and governance requirements., * Own AI-SDLC deployment, operations, and platform reliability (uptime, performance, incident response).

 * Manage infrastructure, monitoring, observability, and operational/on-call support.
 * Build and maintain CI/CD pipelines and automation for platform releases.
 * Drive the shift to a centralised, hosted AI-SDLC service - scalability, multi-tenancy, cost, and resilience.

Must-have technical skills

 * CI/CD - GitLab Pipeline / Jenkins / Harness (highly relevant given your Harness Engineering direction).
 * Infrastructure as Code - Terraform.
 * Cloud platform - AWS (ECS/EKS, Lambda, S3, IAM, networking); container orchestration with Docker + Kubernetes.
 * Observability & monitoring - OpenTelemetry, CloudWatch, logging/tracing for AI workloads.
 * Scripting/automation - Python and/or Bash.
 * Security & compliance operations - secrets management, IAM/least privilege, PCI DSS-aligned controls, auditability.
 * Reliability engineering - SLIs/SLOs, incident management, cost and capacity management (incl. LLM token/credit cost control)., We aim to provide timely updates throughout the process and encourage early applications to ensure consideration.


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