Senior Engineering Manager, International Mobility

About The Team/Role

We are seeking a Senior Engineering Manager with a highly technical, hands-on engineering mindset to lead a team within WEX’s International Mobility Engineering organization. International Mobility is a global team operating across the UK, India, Brazil, and the US. This role requires a leader who can blend technical excellence with strong engineering leadership, fostering a DevOps mindset, Agile execution, and best-in-class software development practices.

As a Senior Engineering Manager, you will be responsible for building scalable, reliable, and secure systems while driving a culture of continuous improvement, automation, and operational excellence. You will partner with engineering teams, product leaders, and business stakeholders to ensure that WEX’s International Mobility products deliver high-performance, cloud-native solutions that meet global business needs.

How you’ll make an impact
• Lead by example with hands-on involvement in architecting, coding, reviewing, testing, and deploying mission-critical software.
• Instill a DevOps culture by championing automation, CI/CD pipelines, and infrastructure-as-code to enhance system reliability and efficiency.
• Promote Agile and Lean engineering best practices, ensuring incremental delivery, iterative improvements, and continuous integration.
• Own the full development lifecycle, from system design and implementation to deployment and monitoring.
• Establish and enforce engineering excellence in code quality, test automation, and observability.
• Drive a data-driven approach to engineering productivity, measuring performance using key engineering and operational metrics.
• Lead a high-performing engineering team, setting clear goals, fostering a culture of accountability, and mentoring engineers.
• Optimize team efficiency by eliminating bottlenecks, improving developer experience, and streamlining workflows.
• Build scalable, fault-tolerant, and secure distributed systems that meet business SLAs and regulatory requirements.
• Collaborate with Product and Business teams to align technical execution with strategic priorities.
• Own and drive technical decisions, balancing trade-offs between speed, scalability, security, and cost.
• Champion engineering best practices for cloud computing, microservices architecture, API-first development, and event-driven systems.
• Ensure system reliability and uptime, leveraging SRE principles, observability tools, and incident management frameworks.

Experience you’ll bring
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 10+ years of experience in software engineering, with at least 3+ years in an engineering leadership role.
• Deep technical expertise in cloud computing platforms (AWS, Azure, or GCP) and cloud-native architectures.
• Strong coding and architectural skills in modern programming languages (Java, Kotlin, Go, Python, or similar).
• Experience leading Agile engineering teams, with a proven track record of delivering software using Scrum/Kanban methodologies.
• Hands-on experience with CI/CD pipelines, Kubernetes, container orchestration, and DevOps automation.
• Proven ability to scale engineering teams and optimize development workflows.
• Expertise in building distributed systems, microservices, and event-driven architectures.
• Deep understanding of API-first development, RESTful and GraphQL APIs, and secure API gateways.
• Strong experience in monitoring, logging, and observability tools (e.g., Prometheus, Datadog, ELK, Grafana, OpenTelemetry).
• Experience working in a fast-paced, high-growth, globally distributed environment.
• Ability to communicate complex technical topics to both engineering and non-engineering stakeholders.
• Experience in financial technology, mobility, or fleet management systems. (Preferred)
• Familiarity with global compliance and regulatory standards for payments and mobility. (Preferred)
• Background in real-time data processing, analytics, or AI-driven optimizations. (Preferred)
• Experience integrating machine learning models or AI-driven decision-making into engineering workflows. (Preferred)