This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Boston, MA; San Francisco Bay Area, CA; Dallas, TX; Salt Lake City, UT; Seattle, WA; and Portland, ME
About the Team/Role
We are seeking a seasoned mid-level Software Engineer in the WEX Mobility Engineering organization. This role will sit in the Mobility team that caters fleet management and mobility payments solutions to our large customers. Mobility development team spans across USA, Brazil, and India. Our Mobility systems provide SaaS and API solutions to various customers. WEX Mobility products enable credit issuance to fleet companies and their workers in the form of WEX or cobranded credit cards, usable at fueling stations and select other merchants. At WEX, we provide fleet managers and operators with fuel discounts, and flexibility to configure spend controls that restrict fleet members to use their cards at configured merchants, for configured amounts and velocity.
How you’ll make an impact:
Design, develop, and maintain robust, scalable, and high-performance object oriented code in our backend services.
Develop public REST APIs using Java and internal gRPC APIs for inter-service and inter-system communication.
Craft systems designs, lead design decisions, and drive alignment with other senior engineers.
Write automated unit tests, integration tests, end-to-end tests, concurrency tests, load/performance tests.
Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.
Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market
Collaborate with cross-functional teams, including product managers, designers, and other engineers, to define and implement new features.
Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid-level engineers, and actively promote engineering best practices.
Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.
Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution
Maintain robust documentation (design docs, run books, change management docs, and readiness plans)
Provide live-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.
Drive cross-team projects as a single-threaded-owner (STO) or tech lead, and actively unblock other engineers to make progress.
Experience you'll bring:
Bachelor’s degree in Computer Science or Software Engineering
3-5 years of professional experience in software engineering.
Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills.
Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets.
Excellent written and verbal communication skills, and a collaborative and empathetic mindset.
Proficiency in backend development, with proficiency expertise in Java or C#, and frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL
Ability to leverage AI-enabled development tools such as Cursor AI, Kiro and GitHub Copilot to accelerate feature delivery, automate documentation, and enhance code quality.
Preferred Qualifications
Master’s degree in computer science or software engineering.
5 years of experience in software engineering.
Experience with event-driven architecture and tools like Kafka.
Experience working on card payments
Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes).
Awareness of API security and PCI DSS compliance requirements
Ability to work on existing codebase, contribute improvements, and adapt to legacy systems’ constraints.
Experience building AI skills & deploying AI solutions to production environments
Experience building production-grade AI agents or copilots
Familiarity with multi-agent systems and distributed AI architectures
Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)
Knowledge of AI evaluation techniques, safety practices, and responsible AI principles
