Summary
✨ AI‑Generated
Join a senior DevOps team building a centralized, secure, cloud-native AWS platform for Data Science and AI/ML workloads. You will design and automate infrastructure, improve delivery practices, and promote platform engineering standards across distributed engineering teams supporting demanding real-time data environments.
Highlights
Technically demanding senior role focused on building a centralized secure AWS platform for Data Science and AI/ML, with exposure to global engineering teams, automation, and platform engineering best practices.
Description
Project description VR-124144
Our client is a global provider of financial market data, managing multiple change programs to deliver high-quality software that connects financial markets worldwide through real-time, high-frequency, low-latency data management systems.
These projects are technically demanding and operate in a dynamic environment.
The Markets and Corporate Engineering Divisions in our Client's company has embarked on a Data Science and AI/ML Transformation Program.
The objective is to establish a new, centralized, and secure cloud-native platform Data Science and AI/ML on AWS to support modern application and infrastructure delivery.
The operating model is a federated model with Core Engineering teams based in London/Bucharest/Bangalore and Engineers embedded within each Business division to drive adoption, automation, and platform engineering best practices.
Responsibilities
As a Senior DevOps Engineer , you will play a key role in designing, building, automating, and supporting cloud infrastructure and deployment pipelines across the Data Science and AI/ML platform.
Design, implement, and manage highly available, secure, and scalable AWS infrastructure using Infrastructure as Code (IaC).
Build, manage, and optimize CI/CD pipelines using GitLab (or equivalent tools) to enable automated application deployment.
Deploy, configure, and maintain containerized applications using Docker and Kubernetes.
Automate operational tasks, deployments, monitoring, and infrastructure provisioning using Python and Terraform.
Collaborate with development, architecture, and platform engineering teams to improve software delivery, reliability, and operational excellence.
Support migration of applications and services to AWS cloud infrastructure.
Implement security best practices, monitoring, logging, and disaster recovery strategies across cloud environments.
Skills
Must have
Strong experience in DevOps engineering (8+ years preferred)
AWS
Strong hands-on experience with AWS services including SageMaker, Bedrock , EC2, VPC, IAM, S3, RDS and EKS,
Python
5+ years of experience developing automation scripts, deployment utilities, infrastructure tooling, and operational automation using Python.
Docker & Kubernetes
Strong experience containerizing applications using Docker.
Hands-on experience deploying and managing Kubernetes clusters (preferably Amazon EKS).
Experience with Helm charts, Kubernetes networking, ingress controllers, autoscaling, and rolling deployments.
Terraform
3+ years of experience provisioning and managing AWS infrastructure using Terraform.
Experience developing reusable Terraform modules and managing remote state.
GitLab CI/CD (or equivalent)
Strong experience designing and implementing CI/CD pipelines using GitLab CI/CD, Jenkins, Azure DevOps, or GitHub Actions.
Experience implementing automated build, test, deployment, and release pipelines.
Nice to have
Hands-on experience in using AI tools (e.g.
GitHub Copilot)
Other
Languages
English: C1 Advanced
Seniority
Senior
