• Implement and deploy complex robotic order fulfillment solutions at customer sites, including the installation and integration of robotic hardware, software, and supporting server infrastructure. • Create and configure SLAM-based maps of warehouse fulfillment centers using AutoCAD or similar CAD software, ensuring accurate representation of the operational environment. • Manage onsite customer relationships, coordinating effectively with both internal teams and external stakeholders to ensure alignment and project success. • Assist with infrastructure setup, robot and software configuration, and provide support during the initial system deployment phase. • Provide on-site customer support following system installation to ensure smooth operation and address any initial issues or adjustments. • Perform other duties as required.

• Designing, building, and maintaining cloud infrastructure, CI/CD pipelines, and deployment automation • Migrating applications from on-prem to GCP • Monitoring web applications and automating daily tasks • Maintaining the production environment • Collaborating closely with development teams, system administrators, and other stakeholders to ensure highly available, secure, and efficient systems

• Lead multiple DevOps teams that support development squads across the organization • Define and drive technical direction, ensuring alignment of cloud and infrastructure strategy • Promote DevOps and platform engineering best practices across teams • Actively contribute as a senior DevOps engineer within one of the teams • Design, build, and optimize cloud infrastructure • Enhance CI/CD processes and improve observability standards • Support complex migrations from on-premises environments to Google Cloud Platform • Collaborate closely with other Team Leads within the department and development teams • Ensure systems are highly available, secure, scalable, and efficient

• Design, build, and maintain scalable, resilient data and ML pipelines, infrastructure, and workflows using tools such as GitHub Actions, ArgoCD, Crossplane, Terraform, Helm, and others. • Automate infrastructure provisioning and configuration management using cloud-native services (preferably AWS) with tools like Terraform, CloudFormation, or Crossplane. • Design, containerize, and manage Kubernetes (EKS) clusters and/or ECS environments in AWS. • Collaborate with development teams to optimize performance, deployment, and cost. • Partner with DevOps and SRE teams to ensure high availability, observability, scalability, and security of the data and ML infrastructure. • Work closely with Data Scientists and ML Engineers to operationalize machine learning models, including building CI/CD pipelines for model training, validation, and deployment. • Implement observability for data pipelines and ML services using tools like Prometheus, Grafana, Datadog, or similar. • Develop and maintain automated pipelines for model retraining, monitoring drift, and versioning in production. • Support experimentation and prototyping in areas such as Machine Learning and Generative AI, transitioning successful prototypes into production systems. • Ensure cloud infrastructure is secure, compliant, and cost-efficient, following best practices in governance, identity, and access management.