Senior Data DevOps Engineer

We are seeking a Senior DevOps Engineer (Data & AI Platforms) . You will build secure cloud foundations for data pipelines and AI workloads, from proof of concept to production. You will own infrastructure as code, CI/CD, monitoring and access controls while partnering with data, machine learning and client network teams. Responsibilities Build and run secure cloud infrastructure for data and AI platforms using infrastructure as code across proof of concept, development, staging and production Enable platforms for data pipelines, model serving, inference and AI agent hosting, including GPU workloads Partner with client network teams to design cloud networking, private connectivity, DNS and firewall controls Implement identity and access management including least-privilege policies, federation and secrets management Create and maintain CI/CD pipelines and release workflows for applications, data pipelines and machine learning models Improve observability through monitoring, logging, alerting and incident response practices Troubleshoot platform issues and optimize reliability, scalability, performance and cost Produce clear architecture documentation, run reviews and support knowledge transfer with delivery teams Requirements Proven experience in DevOps, cloud engineering or platform engineering for production environments Hands-on experience with a major cloud platform: Amazon Web Services (AWS), Microsoft Azure or Google Cloud Platform (GCP) Background in at least one data or AI platform area such as data pipeline infrastructure, model serving, inference or AI agent hosting (for example Databricks, Amazon SageMaker, Vertex AI or Azure AI Foundry) Advanced knowledge of cloud networking including VPC or virtual network design, private endpoints, DNS, VPN connectivity, load balancing and firewall rules Strong knowledge of cloud identity and access management including roles, policies, federation and secrets management plus OAuth 2.0, OpenID Connect (OIDC) or SAML Hands-on experience with Kubernetes, Docker and Linux Proven experience with Terraform or similar infrastructure-as-code tooling Clear communication in English with the ability to explain architecture to technical stakeholders and client teams Nice to have Experience packaging and deploying Python services including dependency management, container builds and private package repositories Exposure to configuration management tools such as Ansible plus Kafka, Elasticsearch/OpenSearch or vector databases Cloud or Kubernetes certifications (AWS, Azure, GCP or Certified Kubernetes Administrator)