GEN AI and AGENTIC AI Engineer

Must Have Technical/Functional Skills
GEN AI & AGENTIC AI build & Implementation experience
•     Hands-on experience with LLMs and RAG architectures
•     Experience with vector databases and semantic search
•     Practical understanding of prompt engineering and evaluation
•     Hands-on experience building agentic or multi-step AI workflows (not just prompting)
•     Experience with orchestration frameworks and tool calling
•     Understanding of AI safety, guardrails, and reliability patterns
•     Ability to operationalize AI agents at enterprise scale
Roles & Responsibilities
•     Build end-to-end GenAI applications using LLMs (text, documents, Q&A, summarization, extraction)
•     Implement RAG pipelines: data ingestion, chunking, embeddings, vector search, and grounded responses
•     Develop APIs and microservices to integrate GenAI solutions with enterprise systems
•     Implement structured outputs, function calling, and prompt frameworks
•     Support evaluation, testing, monitoring, and continuous improvement of GenAI solutions
•     Collaborate closely with the GenAI Architect and Agentic AI Engineers
•     Design and implement agentic AI workflows (planning → execution → observation → iteration)
•     Build tool-using AI agents integrated with APIs, data sources, and enterprise systems
•     Implement multi-agent or orchestrated agent architectures where required
•     Combine Agentic AI with RAG for grounded, enterprise-safe responses
•     Implement guardrails, safety checks, and evaluation mechanisms
•     Debug, optimize, and operationalize agentic workflows in production