Senior Software Engineer - AI Platform

WEX•Boston, MA

1d•Remote

About The Position

At WEX, we’re transforming how businesses operate by embedding advanced AI into our global payments and mobility platforms. The AI Platform Engineering team enables product development groups across WEX to build, deploy, and scale AI-powered experiences quickly and safely. We’re cloud-first, automation-driven, and focused on building reliable, secure, and scalable platforms that make AI a core part of our products. If you’re excited by LLMs, Agentic AI systems, MLOps, and modern DevOps practices—and you thrive in fast-moving teams where innovation meets real-world impact—this role is for you.

Requirements

7+ years of professional software engineering or DevOps/SRE experience, with at least 3+ years working in cloud-native, production environments.
Strong experience with DevOps and GitOps practices, including CI/CD pipelines, automated testing, and environment promotion workflows.
Hands-on experience with Fabric and Argo CD (or similar GitOps tools) for deployment automation and environment management.
Deep, system-administrator-level experience with AWS (preferred) and practical experience with Azure services (compute, networking, IAM, logging, containers).
Proficiency in Python, including writing robust, maintainable code for services, tools, and automation, and comfort with standard Python development workflows.
Familiarity with containerization and orchestration (Docker, Kubernetes, ECS, AKS, or similar).
Experience using AI-native development tools (e.g., Cursor, GitHub Copilot, or similar AI-assisted IDEs) as part of your everyday engineering workflow.
Solid understanding of monitoring, logging, and alerting practices and tools (e.g., CloudWatch, Prometheus, Grafana, Datadog, or similar).
Demonstrated ability to work in agile, collaborative, high-trust engineering teams and to partner effectively with cross-functional stakeholders.
Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.

Nice To Haves

Experience supporting LLM/agentic AI workloads in production (e.g., prompt orchestration, model gateways, vector stores, RAG systems).
Background in financial systems, data compliance, or regulated industries (payments, healthcare, etc.).
Exposure to Terraform or other IaC tools for multi-cloud environments.
Experience building or operating multi-tenant platforms and shared services.
Create, operate, and manage MCP tools and MCP gateways to securely connect AI agents to external systems, enforce governance, and centralize tool access and observability.

Responsibilities

Design, implement, and maintain cloud-native infrastructure for AI and LLM-based applications on AWS and Azure, including networking, compute, IAM, and observability.
Build and manage CI/CD and GitOps workflows using tools such as Fabric, Argo CD, and related DevOps tooling to enable reliable, automated deployments.
Develop production-grade services, utilities, and platform components in Python, including APIs, and automation scripts that support AI workloads.
Implement and maintain Infrastructure-as-Code (IaC) for repeatable environments and services (e.g., Terraform, CloudFormation, or similar tools).
Collaborate with AI/ML engineers and product engineering teams to integrate LLMs and agentic AI capabilities into WEX’s products using secure, scalable patterns.
Operates as a system administrator-level engineer for key cloud services (logging, monitoring, secrets, container orchestration, storage, and security controls).
Champion AI-native development practices by using and promoting tools such as Cursor, GitHub Copilot, and other AI-assisted IDEs to increase velocity and code quality.
Contribute to and refine platform standards for security, compliance, observability, and resiliency across AI services and pipelines.
Participate in on-call rotations and incident response for AI platform components, driving root-cause analysis and continuous improvement.