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)
🏢 ValueCoders
📍 Noida