SDE II - AI Tooling

Summary

Join interface.ai, a leading AI provider for banks and credit unions, as a Software Development Engineer II. In this role, you will design, develop, and maintain AI-powered internal tools to automate workflows and enhance internal efficiencies. You will build and integrate machine learning or NLP components to extract insights and drive decision-making. Collaboration with product, data, and operations teams is crucial to identify opportunities for AI-driven enhancements. The ideal candidate possesses 2-4 years of software engineering experience with proven AI/ML/NLP project involvement. You will leverage JavaScript/Node.js, Python, or related technologies to develop scalable services and APIs.

Requirements

• 2–4 years of experience in software engineering with strong backend development skills
• Proven experience working on at least one AI, ML, or NLP-based application or system
• Proficiency in JavaScript (Node.js) and scripting languages such as Python
• Solid understanding of machine learning workflows, NLP libraries (e.g., spaCy, HuggingFace, NLTK), or LLM integrations
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools like Docker/Kubernetes
• Good understanding of software engineering fundamentals, system design, and application lifecycle
• Excellent analytical and debugging skills, with a problem-solving mindset
• Experience with version control (Git) and CI/CD pipelines
• Strong verbal and written communication skills; ability to work effectively in cross-functional teams

Responsibilities

• Design, develop, and maintain AI-powered internal tools that drive automation and operational intelligence
• Build and integrate machine learning or NLP components to extract insights and drive decision-making across systems
• Collaborate cross-functionally with product, data, and operations teams to identify opportunities for AI-driven enhancements
• Develop scalable services and APIs using JavaScript/Node.js, Python, or related technologies
• Ensure systems are reliable, observable, and maintainable in production environments
• Stay current with emerging trends in AI and apply best practices to real-world business problems

Preferred Qualifications

• Exposure to infrastructure-as-code, observability tools, or performance tuning
• Experience with cloud-native services (e.g., AWS Lambda, S3, SQS, DynamoDB)
• Prior experience in startups or high-growth environments
• Knowledge of financial services or familiarity with core banking systems (a plus, not required)