AWS Cloud DevOps Engineer

At Broadridge, we've built a culture where the highest goal is to empower others to accomplish more. If you’re passionate about developing your career, while helping others along the way, come join the Broadridge team. We are excited to announce an opportunity for AWS Cloud DevOps Engineer to join our organization as part of our AI Enablement Team. In this role, you will play a crucial role in architecting, deploying & supporting the solutions that enhance our AI capabilities across the organization, with a specific focus on GenAI projects.    You will be at the driving innovation and delivering cutting-edge solutions. Your expertise will contribute to the development of our platform, shaping its capabilities and providing impactful solutions.  Join our dynamic team and be part of a collaborative environment that fosters continuous learning and creativity. If you are passionate about machine learning, AI, and want to contribute to the platform capability development for our whole organization, we invite you to apply.    Responsibilities:   Design the ML deploy, monitoring pipelines and engineering infrastructure to support enterprise machine learning systems at scale  Take offline models data scientists build and turn them into a real machine learning production system  Develop and deploy scalable tools and services to handle machine learning training and inference  Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems  Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.  Support model development, with an emphasis on auditability, versioning, and data security  Facilitate the development and deployment of proof-of-concept machine learning systems  Communicate with clients to build requirements and track progress    Qualifications & Skills:   Over all 5-8 years in cloud application development/Administration with at least 4 years of experience in AWS & Terraform, Jenkins, Cloudformation or any other IAAC .  Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools  Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting etc).  Strong hands-on technical skills in automation, infrastructure as code, logging, monitoring and observability, infrastructure configuration, scripting languages and applications.  Experience working in Cloud ecosystem- building and deploying workloads on cloud, preferably AWS.  Associate Certification (preferable) in AWS Development and/or Architect or any cloud related certification (Terraform/chef).  Understanding of AI, ML & Generative AI domain will be an added advantage as the team is focused on creating AIML capabilities for the organization.  Ability to analyze escalations, prioritize, identify owners,…