Senior Systems Engineer

Visa•Ashburn, VA

1d•Hybrid

About The Position

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. The IaaS Systems and Storage & Engineering (ISSE) team is part of the Operations & Infrastructure technology organization. Our vision, mission and purpose are summarized as following, Vision - Deliver best-in-class Infrastructure on demand everywhere. Mission - Engineer and build reliable and secure infrastructure for all type of workloads in Private/ Hybrid Cloud, utilizing open and innovative technologies at the right unit cost. Purpose - increase innovation velocity of developers and reduce infrastructure maintenance overhead. These are the guiding principles for the important work we do every day and build toward the overall vision of Visa - The best way to pay and be paid for everyone, everywhere. You will be part of a team of systems DevOps engineers/architects who adopt, integrate & engineer industry leading technologies and management solutions for the container platform, focusing on Kubernetes, microservices architecture, and cloud technologies. The candidate should have experience in deploying infrastructure solutions on one of major public clouds such as AWS, GCP & Azure. Familiarity with the philosophy of DevOps and experience in infrastructure as code and automation at scale is a must. The candidate will also establish, promote, and provide standard foundational services for Visa's public cloud implementation, closely working with stakeholders to craft and implement solutions with robust security posture, deliver functions with optimized cost, and enhance developer productivity.

Requirements

2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience
Minimum of 3 years of professional experience in cloud infrastructure engineering, DevOps, or site reliability engineering (SRE).
Strong knowledge of operating systems (Linux/UNIX and Windows Server) and scripting languages such as Python, Bash, or PowerShell.

Nice To Haves

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)
Bachelor’s Degree in Computer Science, Information Systems, Engineering, or a related technical discipline.
Proven hands-on experience designing, deploying, and automating infrastructure in major public cloud environments, primary (AWS, Azure, GCP).
Deep understanding of core cloud services including networking, compute, storage, and databases, with experience in multi-account and multi-region configurations.
Proficiency with Infrastructure as Code (IaC) frameworks such as Terraform, Pulumi, or CloudFormation and configuration management tools like Ansible.
Practical experience implementing and maintaining CI/CD pipelines using Jenkins, GitHub Actions, or comparable tools.
Demonstrated ability to design and manage containerized applications and Kubernetes orchestration environments, including GitOps workflows using ArgoCD.
Hands-on experience deploying and monitoring applications with CloudWatch, Azure Monitor, GCP Operations Suite, Prometheus, and Grafana.
Working knowledge of enterprise security best practices, including CIS Benchmarks, IAM policies, vulnerability scanning, and compliance frameworks.
Experience integrating or supporting AI agents within cloud-native applications, including workflow orchestration and tool-calling patterns.
Exposure to Model Context Protocol (MCP) concepts or similar approaches for securely connecting AI agents to enterprise tools, APIs, and data sources.
Familiarity with agentic frameworks (e.g., LangChain, LlamaIndex, or similar) for building multi-step, tool-using AI systems.
Excellent analytical and problem-solving skills with the ability to work independently and collaboratively.
Strong communication and documentation capabilities, with attention to clarity and technical precision.
High initiative, adaptability, and commitment to continuous learning in cloud, DevOps, and AI technologies.
Proven ability to operate effectively in an enterprise environment balancing agility, compliance, and innovation.

Responsibilities

Collaborate with cross-function teams to design, implement, and maintain secure, scalable, and automated cloud infrastructure solutions supporting enterprise-scale systems.
Utilize deep knowledge of AWS, Azure, and GCP to guide infrastructure design decisions aligned with performance, cost, and security goals.
Drive adoption of Infrastructure as Code (IaC) and DevOps methodologies to enable consistent, repeatable deployments and greater operational efficiency.
Develop and manage standard foundational services for the enterprise cloud environment, improving reliability, observability, and cost optimization.
Ensure availability, resilience, and security of mission-critical applications hosted in cloud environments.
Collaborate across engineering, security, and operations teams to mature the cloud ecosystem, integrating logging, monitoring, configuration management, and orchestration tools.
Define, document, and implement enterprise standards and best practices for cloud infrastructure provisioning, automation, and compliance.
Create and maintain reusable IaC modules and CI/CD pipeline templates to advance platform consistency and governance.
Standardize and harden container orchestration platforms, delivering Kubernetes-as-a-Service with automated scaling and high availability.
Integrate cloud monitoring, APM, and SIEM tools to enhance observability, proactive alerting, and security compliance.
Partner with vendors and internal stakeholders to ensure infrastructure meets business, compliance, and security requirements.
Provide technical guidance and mentorship to peers and cross-functional teams on cloud design, automation, and operational practices.
Support the integration of AI and data-intensive workloads into enterprise cloud environments, focusing on performance optimization and scalable automation.