Senior Associate Solutions Designer, AI Engineering

About the role

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description You will be part of a dynamic team of solution engineers who deliver, integrate & architect highly available and scalable infrastructure solutions for on-prem and public clouds, focused on Kubernetes, cloud technologies and automation skills. You will work on innovative solutions that combine deep technical expertise with AI/ML capabilities to drive next-generation solution design and architecture. Essential Functions Develop and architect solutions that are robust and scalable, integrating AI capabilities with Visa's technical ecosystem Develop integrations with AI/ML frameworks, chatbots, and agents to enhance automation Lead technical initiatives leveraging agentic AI, LLMs to automate workflows and improve developer experience Deliver secure, highly available and scalable infrastructure solutions through automation Experienced with docker, container and Kubernetes for container orchestration Hands-on experience in driving the design and implementation of solutions on one of the major public clouds, such as AWS, GCP, Azure with expertise in assessing, developing or migrating well architected applications for containers and cloud Design and build using infrastructure as code and automated testing Develop standard automation templates for deployment of public cloud infrastructure and platform components This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Requirements

• 2 or more years of work experience with a Bachelor's Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
• 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
• 5 or more years of relevant work experience in systems architecture, engineering or development including experience in cloud automation frameworks, Hybrid cloud infrastructure deployments with a bachelor's degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
• Experience with AI agent frameworks, LLMs, or generative AI applications (Claude, GPT, etc.)
• Knowledge of AI-powered development tools (Claude Code, GitHub Copilot, etc.) or building similar systems
• Experience applying AI to solve engineering challenges and converting business processes into automated agentic workflows
• Experience in designing, building, and running production systems in cloud or migrating to the cloud and or containers, practicing infrastructure as code, automated testing, and automating infrastructure tasks
• Automation championing through robust automation using Python, Java, and Go to streamline end-end delivery of automated application deployment
• Best in class Software Developer including Continuous Integration and Continuous Deployment (CICD) pipeline tools such Jenkins and proficient in git
• Solid understanding of Linux/Unix systems, networking protocols, certificate management, secret management, system design, cloud platforms (AWS, Azure, GCP), and containerization (Kubernetes, Docker)
• Experience with cloud platforms (AWS, Azure, GCP) and modern architectures
• Knowledge of API design, microservices, and distributed systems
• Demonstrated experience with hands-on Infrastructure as Code (IaC) development and deployment in Hybrid Cloud (AWS, Azure and GCP) deployments
• Knowledge of AI/ML and Generative AI algorithms, and their architectural design
• Proficient with container deployments and troubleshooting in Kubernetes environments
• U.S. Applicants Only
• Work Hours
• Varies upon the needs of the department.
• Travel Requirements
• This position requires travel 5-10% of the time.
• Mental/Phy

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