AI Software Engineer II (Credit)

NCC provides software, credit, compliance, and data solutions for the automotive industry. The AI Software Engineer II will develop and deploy production-ready AI-powered features using large language models, machine learning, and cloud AI services. The role involves building scalable backend services, data pipelines, and integrations while collaborating with Product and Engineering teams.

Responsibilities:

• Design, build, and deploy AI-powered features within our SaaS platform
• Integrate LLMs and cloud AI services into production applications
• Develop scalable backend services, REST APIs, and application integrations
• Build and maintain data pipelines that support AI workflows
• Contribute across the application stack, including backend services and frontend enhancements as needed
• Collaborate with Product Managers, UX Designers, and Software Engineers to deliver customer-centric solutions
• Rapidly prototype new AI capabilities and iterate on customer feedback
• Write clean, maintainable, well-tested code that follows software engineering best practices
• Optimize application performance, scalability, and reliability
• Participate in code reviews and contribute to architectural decisions

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or equivalent practical experience)
• 2–4 years of professional software engineering experience
• Experience developing applications with Python, C#, Java, JavaScript, or similar object-oriented languages
• Experience with consuming or integrating LLMs and AI services via APIs
• Experience building RESTful APIs and backend application services
• Working knowledge of cloud platforms, including AWS, Azure, or Google Cloud
• Experience with Git and modern software development practices
• Understanding of databases and data modeling (SQL and/or NoSQL)
• Strong analytical and problem-solving skills
• Excellent collaboration and communication skills
• Experience with Retrieval-Augmented Generation (RAG)
• Experience using vector databases and embeddings
• Familiarity with AI orchestration frameworks such as LangChain or LlamaIndex
• Experience building data pipelines and AI workflows
• Experience deploying containerized applications with Docker and Kubernetes
• Exposure to CI/CD pipelines and DevOps practices
• Experience developing customer-facing SaaS applications