• Design, implement, and manage highly available infrastructure for our cloud-based platforms (AWS). • Work with our internal engineering teams to architect and support AI/ML infrastructure, specifically managing AWS Lambda infrastructure, and some legacy SageMaker environments for model training, hosting, and inference. • Create and automate robust deployment pipelines using CI/CD tools (GitLab / GitHub Actions) for both web applications and machine learning models. • Build, maintain, and scale containerized applications with Docker and ECS/Fargate. • Implement MLOps best practices to streamline the transition of models from development to production. • Ensure system scalability and reliability through proactive monitoring, logging, and automated alerting. • Collaborate with both Product Engineers and Data Scientists to optimize performance, security, and infrastructure costs. • Manage and evolve our Infrastructure as Code (IaC) footprint.

• Assist in building, maintaining, and improving CI/CD pipelines in GitLab, with exposure to SAP platforms. • Support the automation of deployment, monitoring, and remediation processes under the guidance of senior engineers. • Help document CI/CD pipelines, templates, and operational procedures. • Participate in implementing DevSecOps best practices, including basic security and compliance checks. • Collaborate with infrastructure, security, and application teams to support on-prem (VMware) and cloud environments (GCP / Kubernetes). • Monitor pipelines and systems, troubleshoot issues, and escalate when necessary. • Continuously learn DevOps tools, cloud technologies, and automation practices.

• Design, build, and operate production Kubernetes clusters on bare-metal infrastructure. • Implement and operate custom Kubernetes networking solutions. • Develop and maintain custom Kubernetes operators and controllers. • Deploy and optimize NVIDIA GPU operators and custom scheduling logic for GPU workloads. • Build deep integrations between Kubernetes and underlying infrastructure. • Design and implement automation using Terraform, Ansible, Helm, and custom operators. • Manage production bare-metal infrastructure across multiple regions ensuring high availability, fault tolerance, and graceful degradation. • Build comprehensive monitoring, logging, and alerting using Prometheus, Grafana, and ELK stack. • Identify and resolve performance bottlenecks across infrastructure domains.

• Continuously assess technology hosted in the public cloud against industry standards and security compliance. • Streamline Infrastructure platforms to 100% “everything as code" in the public cloud. • Write code once and reuse it as much as possible for Infra as code, CICD pipelines, templates, etc. • Implements end-to-end automated CICD practices for build, scan, packaging, test, and deployment. • Drive Containerization across application workloads to leverage native cloud features and scalability. • Achieve 100% compliance on all infrastructure vulnerabilities and package vulnerabilities. • Drive 100% self-service and reusable automation across stakeholders for platform requests. • Add instrumentation across Infrastructure for monitoring and alerting on internal problems. • Build processes and diagnostic tools to troubleshoot, maintain, and optimize Infrastructure. • Adopt continuous learning of modern data engineering practices. • Maintain industry standards through incremental adoption of new technology and best practices. • Create and continuously maintain high-quality documentation for platform and DevOps practices.