Hybrid Software Engineer 2 – AI Platform

at WEX

• Job title: Software Engineer 2 – AI Platform
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: $96,100 - $115,500 per year
• Degree requirement: Bachelor's Degree
• Tech skills: GRPC, Java, Spring Boot, SpringBoot, SQL
• Location requirements: Hybrid, Boston, United States

About the role

• Software Engineer developing AI platform solutions at WEX, enhancing operational efficiencies through scalable and maintainable backend services. Collaborating with cross-functional teams to build and optimize advanced AI technologies.

Responsibilities

• 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.
• Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution within Mobility platforms.
• Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.
• Implement and scale multi-agent architectures to support complex, distributed use cases across payments and fleet ecosystems.
• Integrate systems using Model Context Protocol (MCP) or similar frameworks to enable secure and scalable interaction between AI agents, APIs, and enterprise data sources.
• Build and optimize LLM-powered services (e.g., OpenAI APIs, LangChain) for production-grade performance, reliability, and cost efficiency.
• Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and compliance of AI-driven systems.
• Design solutions for context management, memory, and retrieval-augmented generation (RAG) to enhance agent effectiveness.

Requirements

• Bachelor’s degree in Computer Science or Software Engineering
• 2–5 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 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

Benefits

• health, dental and vision insurances
• retirement savings plan
• paid time off
• health savings account
• flexible spending accounts
• life insurance
• disability insurance
• tuition reimbursement