AI/ML EngineerTechnical/Functional Skills Role Summary Codes and integrates AI/ML outputs into applications using traditional SDLC practices without automated ML pipelines. Includes engineer focused on UI/UX. Uses AI Agents effectively to accelerate delivery.Key Responsibilities:Build full-stack applications that integrate AI/ML outputs into user-facing and backend workflows.Develop APIs and services that orchestrate model inference, prompt flows, and agent/tool integrations.Leverage AI coding assistants (e.g., GitHub Copilot, agentic IDEs) to accelerate delivery while maintaining quality.Implement UI/UX experiences for AI-enabled features (explanations, feedback loops, human-in-the-loop controls).Apply secure SDLC practices: code reviews, testing, dependency management, and vulnerability remediation.Partner with architects and platform teams to align to standards and reuse shared components.Required Qualifications:5+ years building production software (backend and/or frontend) in Java/Python/.NET ecosystems.Experience with web frameworks and modern UI (React or similar) and REST API development.Working knowledge of CI/CD, Git workflows, and automated testing.Comfort integrating with ML services, LLM/agent runtimes, or data platforms via APIs.Strong problem-solving skills and ability to deliver iteratively in an agile environment.Preferred / Nice to Have:Experience building internal tools or copilots with prompt engineering and tool/function calling.Experience with observability for AI features (quality metrics, prompt/model versioning).UX experience designing AI interactions and feedback capture.Core Skills (from POD sheet) Java/Python/.NET, Git, REST APIs, CI/CD basics, React; GH Copilot, Claude Code (or agentic IDE)