Generative AI Specialist

Design, develop, and deploy Generative AI applications using Large Language Models (LLMs). Build and optimize Retrieval-Augmented Generation (RAG) pipelines to enable accurate, context-aware responses based on enterprise data. Develop and implement AI agents and multi-agent systems using Agentic AI frameworks. Integrate LLMs with internal systems, APIs, databases, and external tools. Implement prompt engineering techniques, context management, and model fine-tuning when required. Work with vector databases and embedding models to improve information retrieval and semantic search.

Preferred Qualifications

• Experience with LLM fine-tuning, PEFT, LoRA, or quantization
• Experience implementing advanced RAG techniques, including hybrid search, reranking, and query expansion
• Knowledge of AI safety, guardrails, hallucination mitigation, and LLM observability
• Experience building production-grade multi-agent systems and autonomous workflows
• Familiarity with MLOps or LLMOps practices

Desired Candidate Profile

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, or a related field. 1-5 years of experience in AI/ML, Software Engineering, or a related technical field, with practical experience in Generative AI development. Strong programming skills in Python. Hands-on experience working with Large Language Models (LLMs), such as GPT, Claude, Gemini, or open-source models (Llama, Mistral). Solid experience designing and implementing Retrieval-Augmented Generation (RAG) architectures. Practical experience with embeddings, semantic search, vector databases, and document processing. Hands-on experience developing AI agents and agentic workflows.

Preferred Qualifications

• Experience with LLM fine-tuning, PEFT, LoRA, or quantization
• Experience implementing advanced RAG techniques, including hybrid search, reranking, and query expansion
• Knowledge of AI safety, guardrails, hallucination mitigation, and LLM observability
• Experience building production-grade multi-agent systems and autonomous workflows
• Familiarity with MLOps or LLMOps practices