Senior Backend Engineer – AI Platform

WEX is a leading company in the fintech sector, seeking a Senior Backend Engineer for their AI Platform team. The role involves architecting and developing next-generation AI-driven solutions, focusing on building autonomous AI agents and scalable backend services.

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
• 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