Senior Platform Engineer, DSP&Automation

<p><strong>Role Overview<br><br></strong>We are looking for a</p><p><strong>Role Overview<br><br></strong>We are looking for a<strong>Senior Technology Engineer</strong>to drive<strong>platform stability, automation, and operational excellence</strong>within the Data Science Platform (DSP).<br><br>This is not a support role — this is a<strong>hands-on engineering role</strong>where you own automation, orchestration, and reliability across a<strong>hybrid cloud ecosystem (OpenShift + AWS/Azure/GCP)</strong>.<br><br>You will be the backbone of DSP operations — if things break, scale poorly, or require manual intervention, that's your problem to eliminate permanently.<br><br><strong>Requirements<br><br></strong><strong><strong>Key Responsibilities<br><br></strong></strong><strong><strong>Platform Engineering&Operations<br><br></strong></strong><ul><li>Own end-to-end technical operations of DSP infrastructure</li><li>Ensure high availability, performance, and scalability of platform services</li><li>Monitor system health, troubleshoot issues, and implement permanent fixes (not patchwork)<br><br></li></ul><strong><strong>Automation&Orchestration<br><br></strong></strong><ul><li>Design and implement automation frameworks to eliminate manual processes</li><li>Build CI/CD pipelines and automate deployment workflows</li><li>Drive infrastructure-as-code (IaC) adoption using tools like Terraform/Ansible<br><br></li></ul><strong><strong>Container&Cloud Platform Management<br><br></strong></strong><ul><li>Manage and optimize OpenShift / Kubernetes environments</li><li>Work across multi-cloud (AWS, Azure, GCP) infrastructure</li><li>Ensure efficient resource utilization and cost optimisation<br><br></li></ul><strong><strong>MLOps / Data Platform Support<br><br></strong></strong><ul><li>Enable smooth ML model deployment and lifecycle management</li><li>Support tools like OpenShift AI, SageMaker, or similar platforms</li><li>Ensure reproducibility and reliability of data science workflows<br><br></li></ul><strong><strong>Monitoring&Reliability<br><br></strong></strong><ul><li>Implement monitoring using Prometheus, Grafana, ELK stack</li><li>Define SLAs, SLOs, and ensure platform meets reliability standards</li><li>Drive proactive incident prevention (not reactive firefighting)<br><br></li></ul><strong><strong>Collaboration&Governance<br><br></strong></strong><ul><li>Work closely with Data Scientists, DevOps, and Platform teams</li><li>Ensure adherence to security, compliance, and governance standards</li><li>Act as a technical SME for DSP operations<br><br></li></ul><strong>Mandatory Skills (Non-Negotiable)<br><br></strong><ul><li>Strong experience in OpenShift / Kubernetes</li><li>Hands-on experience in multi-cloud environments (AWS/Azure/GCP)</li><li>Expertise in automation (Terraform, Ansible, Jenkins, GitOps)</li><li>Strong knowledge of CI/CD pipelines and DevOps practices</li><li>Experience in Python or scripting (Bash/Shell)</li><li>Experience with monitoring tools (Prometheus, Grafana, ELK)<br><br></li></ul><strong><strong>Good to Have<br><br></strong></strong><ul><li>Experience in MLOps / AI platforms (OpenShift AI, SageMaker, Bedrock)</li><li>Exposure to LLM deployment / inference platforms (vLLM, Triton, etc.)</li><li>Knowledge of data pipelines and big data ecosystems</li><li>Banking or financial services experience<br><br></li></ul><strong>Experience Required<br><br></strong><ul><li>6-10 years of relevant experience in Platform Engineering / DevOps / Cloud Engineering</li><li>Proven experience managing enterprise-scale platforms</li></ul></p>#J-18808-Ljbffr