LLM Development & Fine-Tuning
Fine-tune large language models on domain-specific datasets.
Optimize prompts and context strategies to maximize performance across diverse use cases.
Implement and evaluate RAG (Retrieval-Augmented Generation) pipelines for knowledge-grounded AI responses.

Multi-Agent Orchestration
Build and manage multi-agent AI systems using frameworks such as LangChain, AutoGen, CrewAI, and Haystack .
Design intelligent workflows where multiple AI agents collaborate, coordinate, and reason effectively.

Knowledge Graphs & Reasoning
Construct and maintain knowledge graphs to enhance contextual reasoning and factual grounding of LLMs.
Integrate graph-based reasoning with LLM pipelines for improved interpretability and accuracy.

Evaluation & Safety
Develop robust evaluation pipelines for hallucination detection, factual alignment, safety, and ethical compliance .
Define metrics and benchmarks for continuous monitoring and quality assurance of deployed models.

📌 Llm Engineer Noida (India)
🏢 ValueCoders
📍 India