Develops AI application services, APIs, and integration layers that consume LLMs, ML models, and retrieval services
Designs and implements the front-end of AI applications — responsive, accessible user interfaces and conversational/chat experiences — from UX wireframes through production code
Implements GenAI application patterns including retrieval-augmented generation (RAG), agents, tool/function calling, prompt templates, and streaming responses (including streaming UI)
Applies production-grade engineering practices end-to-end (front-end and back-end): code quality, unit and integration testing, CI/CD, secure coding, and secret management
Integrates AI applications with banking data and platform components — APIs, event streams, message queues, batch pipelines, and SSO/IAM
Implements guardrails and safety across the application layer, including PII redaction, content filters, output validation, fallback behaviors, and safe rendering of model output in the UI
Builds observability into every service and interface: structured logging, metrics, tracing, prompt/response logging, token and latency telemetry, and front-end performance monitoring
Contributes to runbooks, support playbooks, and the on-call rotation during the stabilization period
Collaborates with Data Scientists and ML Engineers to operationalize models, prompts, and evaluation hooks, and supports incident troubleshooting and continuous improvement after go-live
Plans and delivers AI application modules and front-end components with increasing independence, assessing technical feasibility for new GenAI features and supporting integrations
Introduces engineering best practices and new GenAI techniques to the team, and shares knowledge through code reviews, tech talks, and internal communities
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Qualifications
Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field (or equivalent practical experience
At least 3 years of software engineering experience building and operating production web applications, services, and API
Strong proficiency in Node.js / TypeScript as the primary stack, with Python as a secondary language
Front-end design and implementation experience: a modern framework (React, Angular, or Vue), HTML/CSS, responsive and accessible UI, and component-based architecture.
Hands-on experience with REST APIs, Git, CI/CD pipelines (Azure DevOps or GitHub Actions), containerization (Docker), and automated testing (front-end and back-end).
Familiarity with LLM application concepts: prompt design, RAG, embeddings/vector search, function/tool calling, and building streaming/chat UI
Understanding of secure coding practices, safe handling of sensitive data (PII), and front-end security (XSS, safe rendering of model output)
Exposure to at least one major cloud platform — Microsoft Azure preferred (Azure OpenAI, Azure AI Search, AKS a strong plus)
Experience in banking, financial services, or other regulated environments is an advantage
Comfortable working in an Agile / Scrum environment