Data Scientist - Agentic AI

The AI Engineer will build, optimize, and deploy production-grade AI solutions with a focus on LLM-based applications including RAG, agentic workflows, and fine-tuning models. Responsibilities include developing and maintaining LLM-powered applications using frameworks like LangChain, LangGraph, and LlamaIndex, implementing RAG pipelines, developing autonomous agents, executing fine-tuning and optimization tasks, deploying models using Docker and Kubernetes, maintaining CI/CD pipelines, and ensuring data privacy and compliance. The professional will play a key role in driving data-driven decision-making efforts, ensuring models and pipelines remain scalable, well-documented, and aligned with evolving business priorities. Strong emphasis is placed on model validation, thorough testing, and proactive issue resolution to ensure reliable, high-quality outputs across the organization.

3-7 years of experience in Software Engineering or Data Science with at least 2 years focused on deploying AI/ML models in production. Expert-level Python skills, hands-on experience with LLMs and vector databases, strong cloud and containerization experience, and strong SQL and API design skills. Any Graduate or LLM in Law. Familiarity with change management practices and a track record of successful stakeholder engagement across diverse business units is preferred. Prior experience mentoring junior team members and contributing to internal knowledge repositories will also be viewed favorably.