Applied Scientist

Role Overview

As an Applied Scientist Agentic AI & Automation, you will design and build intelligent, agent-based systems that improve data workflows and operational efficiency. This role blends LLM-powered agents, classical machine learning, and rapid experimentation, enabling ideas to move efficiently from concept to production.

Key Responsibilities

Agentic AI & LLM Systems (Core Responsibility)

• Design and implement Agentic AI workflows using Large Language Models (LLMs) and tool based reasoning.
• Build intelligent agents capable of decision-making, orchestration, and task automation.
• Apply and evaluate techniques including: Prompt engineering and fine-tuning, Retrieval-Augmented Generation (RAG), Ranking, classification, and hybrid ML approaches
• Assess agent performance, robustness, and scalability in production-like environments.

AI & Automation Exploration

• Explore AI-driven approaches for data analysis, validation, and intelligent recommendations.
• Identify automation opportunities across communication workflows and internal portals.
• Design AI-assisted workflows to reduce manual effort and accelerate operational processes.