MLOps Automation Engineer Lead

Description Summary: Our Enterprise Data and Analytics department is growing, and we're looking for an outstanding MLOps Automation Engineer Lead to join our team. At Huntington, this is an opportunity to work cross-functionally with nearly every team in the company to elevate the organization by uncovering trends and opportunities, decreasing the time to insight, and making data accessible to all. Our goal is to be the Best performing Regional Bank in America, and we need data and analytics to meet that goal.  As we advance our data and analytics capabilities, we want individuals interested in leading and developing current team members, while also serving as a technical leader who will still be involved in deploying data and models to production. The primary focus is automating development and delivery processes and maintaining the continuous integration and continuous deployment (CI/CD) pipeline.

Streamline the data, analytics, and model development lifecycle by identifying pain points and productivity barriers and determining ways to resolve them through automation. Understand the current process and technical complexities of developing and deploying data pipelines and model builds and develop automation solutions to improve and extend the existing process to become an unattended delivery pipeline. Collaborate closely with product development, architecture, data engineering and testing teams to understand their current build and release processes and make recommendations for improvement through the automation of various tasks. Partner with cross-functional stakeholders, including development, operations, quality assurance and security, to streamline processes. Develop and continuously improve automation solutions for containerized workloads on AWS EKS to enable teams to build and deploy quality data and code efficiently and consistently. Build automated testing solutions in support of quality management objectives to reduce manual effort. Build automated environment provisioning solutions leveraging AWS EKS and Terraform in response to changes in processing demand. Build automated feedback mechanisms to monitor the performance of models in production. Design and maintain AWS EKS infrastructure for ML model deployment, including containerization strategies, resource optimization, OAuth 2.0 integration, security posture management, and disaster recovery planning. Design and implement backup, disaster recovery, and business continuity solutions for EKS workloads. Implement and maintain secure authentication and authorization mechanisms using OAuth 2.0 within Kubernetes environments. Work closely with cross-functional stakeholders to analyze and troubleshoot complex production issues. Prepare and present design and implementation documentation to multiple stakeholders. Promote automation across the data management and analytics delivery organization. Provide leadership, coaching, and mentoring to team members and develop team to work with all areas of the organization. Work with stakeholders to ensure that business needs are clearly understood and that services meet those needs. Anticipate and analyze trends in technology while assessing the emerging technology’s impact(s). Coach individuals and teams through change and serve as a role model. Perform other duties as assigned.

Bachelor’s Degree (Computer Science, Business Administration, Economics or related fields) or equivalent relevant work experience 7+ years’ experience in automation engineering, software engineering, or related field 7+ years’ experience with one or more coding languages (e.g., JavaScript, C++, Python, Java), CI/CD tools (e.g., Jenkins, Artifactory, CircleCI, Ansible), and development platforms (e.g., AWS, Azure, Docker, Kubernetes) Preferred Qualifications: 3+ years' hands-on experience with Kubernetes, including understanding of core objects (namespaces, deployments, pods,