About the Team/Role

WEX is an innovative global commerce platform and payments technology company looking to forge the way in a rapidly changing environment, to simplify the business of doing business for customers, freeing them to spend more time, with less worry, on the things they love and care about. We are journeying to build a consistent world-class user experience across our products and services and leverage customer-focused innovations across all our strategic initiatives, including big data, AI, and Risk. Our AI Infrastructure team is pivotal in enabling these advancements.

We are looking for a highly motivated and high-potential Engineer to join our AI Infrastructure team to make significant contributions to our cloud-based AI solutions and grow your career.

This is a really exciting time to be in the AI Infrastructure team at WEX. Our team is responsible for building and maintaining the robust, scalable, and secure cloud infrastructure that powers our AI and machine learning initiatives. We work with cutting-edge technologies like AWS, Azure, Docker, and Kubernetes to create a dynamic environment that supports the development and deployment of AI models at scale.

We have challenging problems with huge business impact potential for you to work on and grow. We also have a strong team with highly talented and skillful engineers and leaders to support, guide, and coach you.

If you dream to be a strong engineer who can solve tough problems, generate big impacts, and grow fast, this is a great opportunity for you!

How you’ll make an impact

• Collaborate with partners/stakeholders to understand the requirements of our AI development teams and key challenges.

• Design, build, and maintain cloud infrastructure on AWS and Azure to support AI/ML workloads.

• Implement and manage containerization technologies (Docker) and orchestration platforms (Kubernetes).

• Develop and maintain CI/CD pipelines for automating the deployment and management of AI infrastructure.

• Develop and maintain monitoring and alerting systems to ensure the health and performance of production AI infrastructure.

• Analyze system performance data to identify bottlenecks and opportunities for improvement.

• Mentor and learn from your peers, foster continuous learning of new cloud technologies and best practices.

• Get good at our team’s processes and best practices and apply them to given tasks with help from peers and your manager. Make sure to understand the underlying problems you try to solve with these tasks, and your implementations effectively address these problems in a reliable and sustainable way.

• Partner with team members in development and problem-solving.

• Independently complete work and proactively seek reviews from senior engineers on your work to ensure high quality.

• Perform technical discussions. Proactively review work from peers and learn.

Experience you’ll bring

• Bachelor's degree in Computer Science, Software Engineering, or a related field.  OR demonstrable equivalent deep understanding, experience, and capability.

• A Master's or PhD degree in Computer Science (or related field) is a plus.

• 2+ years of experience in software engineering or cloud infrastructure, with a focus on supporting AI/ML workloads.

• Demonstrable strong programming skills in a 3GL strongly-typed language like Java, Python, C/C++ or Golang.

• Strong understanding of cloud platforms (AWS and Azure), including services relevant to AI/ML (e.g., EC2, S3, EKS, Azure ML, AKS).

• Hands-on experience with containerization (Docker) and container orchestration (Kubernetes).

• Experience with building and managing CI/CD pipelines for infrastructure and ML model deployment (using tools like Jenkins, GitLab CI/CD, etc.).

• Strong understanding of networking concepts (VPC, subnets, routing, firewalls) and experience configuring network infrastructure in the cloud.

• Experience with infrastructure monitoring and alerting tools (e.g., Prometheus, Grafana, CloudWatch, Azure Monitor).

• Strong scripting skills (Python, Bash) for automation and configuration management.

• Excellent problem-solving skills, with the ability to analyze complex systems and identify performance bottlenecks.

• Strong communication and collaboration skills, with the ability to work effectively in a team environment.