Job Description
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 Salary Range: $130,000 to $170,000 per year