Description

You will design and productionize agentic AI systems and LLM applications, owning the full lifecycle from statistical modeling to deployment.

This role is on-site.

Responsibilities

• Build and deploy AI agents and multi-agent systems using LangGraph, LangChain, and Semantic Kernel.
• Architect and productionize RAG solutions, including retrieval pipelines and ranking strategies for enterprise LLMs.
• Develop machine learning models for classification, regression, forecasting, recommendations, and anomaly detection.
• Implement NLP solutions such as text classification, entity extraction, semantic search, and conversational AI.
• Apply statistical modeling and experimental design to validate performance and drive data-driven decisions.

Required Skills

• 6-7 years of experience in Data Science and end-to-end ML solution development.
• Strong background in Statistical Analysis: probability, hypothesis testing, regression, Bayesian statistics, and A/B testing.
• Hands-on expertise in NLP and LLM development for semantic understanding and language tasks.
• Proven experience with Agentic AI and RAG architectures for enterprise applications.
• Proficiency in AI/ML frameworks and tools.
• Ability to design complex retrieval pipelines and ranking strategies.
• Strong communication skills to translate technical findings into business value.

Preferred Skills

• Experience with Deep Learning and Generative AI techniques.
• Background in Semantic AI applications.

Key Skills

Education

Any Graduate