AI/ML Integration Engineer

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.

Job Description

• 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.

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.
• 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.