- Design & Develop Agentic AI Solutions: Build autonomous AI agents capable of orchestrating workflows, decision-making, and multi-step reasoning.
- Generative AI Applications: Implement LLM-based solutions for code generation, document automation, and conversational AI.
- AI Use Case Execution: Lead development for prioritized use cases in areas like Copilot integration, predictive analytics, ITSM automation, and data engineering pipelines.
- Innovation & Research: Explore emerging AI frameworks (LangChain, AutoGen, CrewAI) and integrate them into enterprise-grade solutions.
- Collaboration: Work with cross-functional teams to understand use case/design and ensure seamless deployment and scalability of AI solutions.
- Documentation & Knowledge Sharing: Create reusable assets, best practices, and contribute to AI governance frameworks.
Required Skills & Experience:
- Core Expertise:
- Agentic AI frameworks and multi-agent systems
- Generative AI (LLMs, prompt engineering, RAG)
- AI orchestration tools and libraries
- Programming: Python (mandatory), experience with APIs, microservices, and cloud platforms (Azure/AWS/GCP).
- Enterprise AI Tools: GitHub Copilot, Azure OpenAI, LangChain, HuggingFace.
- Domain Knowledge: Exposure to SAP Automation, Data Engineering/ETL, Predictive Analytics is a plus.
- Experience: 5+ years in AI/ML development, with at least 2 years in Generative AI and Agentic AI projects.
- Soft Skills: Strong problem-solving, communication, and ability to work in a fast-paced, collaborative environment.
Preferred Qualifications:
- Hands-on experience in building autonomous AI agents for enterprise workflows.
- Knowledge of AI governance, security, and compliance.
- Familiarity with AI-driven productivity tools (e.g., Microsoft Copilot, SAP Joule AI).
