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About the Role
We are seeking a seasoned Sr. Software Engineer to join the Platform team, focusing on building an AI Platform to support feature development. You will architect and realize our next-generation Agentic AI Platform, designing, developing, and deploying autonomous AI agents, skills, and MCP servers. This role operates at the forefront of generative AI, distributed systems, and fintech, empowering WEX to deliver intelligent, proactive solutions globally.
Responsibilities
- Design, develop, and maintain robust, scalable, and high-performance object-oriented code in backend services.
- Develop public REST APIs using Java and internal gRPC APIs.
- 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, and 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, and continuous integration and deployment.
- Collaborate with cross-functional teams to define and implement new features.
- Conduct code reviews, mentor junior and mid-level engineers, and promote engineering best practices.
- Troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure performance and reliability.
- Conduct comparative analyses of competing technologies to advise the team on solutions.
- Maintain robust documentation, including 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 or tech lead, and unblock other engineers.
- Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution.
- Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.
- Implement and scale multi-agent architectures.
- Integrate systems using Model Context Protocol (MCP) or similar frameworks.
- Build and optimize LLM-powered services for production-grade performance, reliability, and cost efficiency.
- Implement evaluation frameworks, observability, and guardrails for AI-driven systems.
- Design solutions for context management, memory, and retrieval-augmented generation (RAG).
Requirements
- Bachelor’s degree in Computer Science or Software Engineering
- 5–8 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 expertise in Java or C#, frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL
- Hands-on experience building or contributing to AI/LLM-powered applications or agent-based systems
- Familiarity with agent frameworks, tool-use patterns, and orchestration of LLM workflows
- Experience integrating AI systems with external tools/APIs using MCP or similar protocols
- Understanding of prompt engineering, embeddings, and vector-based retrieval systems
- Experience designing systems for scaling AI workloads in production environments
- Master’s degree in computer science or software engineering
- 8+ years of experience in software engineering
- Experience with Python, Java, 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
Skills
- Java
- C#
- SpringBoot
- RESTful APIs
- ODATA framework
- SQL
- Python
- Kafka
- Docker
- Kubernetes
- Agentic AI
- LLM
- MCP
- Prompt Engineering
- Embeddings
- Vector-based retrieval systems
- Vector databases
- AI evaluation techniques
- AI safety practices
- Responsible AI principles
Location
- Remote
- Boston, MA
- San Francisco Bay Area, CA
- Dallas, TX
- Salt Lake City, UT
- Seattle, WA
- Portland, ME
Work Type
- Remote
- Full-time
Experience Level
- Senior
- 5-8 years
- 8+ years
Education Level
- Bachelor's degree in Computer Science or Software Engineering
- Master's degree in computer science or software engineering
Salary/Compensations
- $121,500.00 - $145,500.00
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Retirement savings plan
- Paid time off
- Health savings account
- Flexible spending accounts
- Life insurance
- Disability insurance
- Tuition reimbursement
About the Company
- Our Platform team is dedicated to architecting scalable, robust, and maintainable UI and API platform solutions that empower internal feature development teams to build at velocity. Within the NAM Mobility ecosystem, our products facilitate strategic credit issuance to fleet organizations and their workforce through WEX-branded or co-branded credit instruments, accepted across a vast network of fueling stations and merchant partners. We provide fleet managers and operators with advanced spend orchestration capabilities, encompassing fuel discounts and sophisticated spend controls that permit precise configuration of merchant restrictions, transaction limits, and velocity thresholds to optimize operational efficiency.