Cloud Data Science Lead

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 Qualification:-

- 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.

Skills:-

Java/Python/.NET, Git, REST APIs, CI/CD basics, React; GH Copilot, Claude Code (or agentic IDE)