GenAI Platform DevOps Engineer (AWS)

Broadridge Financial Solutions

Greater London

Hybrid

GBP 85,000 - 120,000

Full time

7 days ago
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Job summary

Broadridge Financial Solutions is seeking an AWS Cloud DevOps Engineer to join our AI Enablement Team in London. You will design ML deploy/monitoring pipelines, develop scalable tools, and productionize offline models.

You will drive automation, CI/CD, and security across enterprise ML systems, collaborating with data scientists and clients to turn concepts into reliable solutions. The role emphasizes GenAI projects, platform capability development, and a hybrid work model, offering

Qualifications

  • 5–8 years in cloud app development/administration, with AWS.
  • 4+ years AWS, Terraform, Jenkins, CloudFormation or similar IAAC.
  • Experience building end-to-end Platform/ML DevOps on AWS Sagemaker or similar.
  • CI/CD, automation, logging, monitoring, and observability.
  • Scripting languages, infrastructure as code, security basics.
  • Strong communication in remote/multicultural teams.

Responsibilities

  • Design ML deployment, monitoring pipelines and infra to support enterprise ML systems.
  • Turn offline models into production ML systems.
  • Develop and deploy scalable ML training and inference tools.
  • Identify new technologies to improve performance and reliability.
  • Apply software engineering best practices to ML, including CI/CD and automation.
  • Support model development with auditability, versioning and data security.
  • Facilitate deployment of proof-of-concept ML systems.
  • Communicate with clients to build requirements and track progress.

Skills

AWS
CI/CD
Automation
Shell scripting
Communication

Education

Associate AWS Certification

Tools

Terraform
Jenkins
CloudFormation
Docker
Kubernetes
GitLab
Chef
Python

Job description

Broadridge Financial Solutions is seeking an AWS Cloud DevOps Engineer to join our AI Enablement Team in London. You will design ML deploy/monitoring pipelines, develop scalable tools, and productionize offline models.

You will drive automation, CI/CD, and security across enterprise ML systems, collaborating with data scientists and clients to turn concepts into reliable solutions. The role emphasizes GenAI projects, platform capability development, and a hybrid work model, offering

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