Applied Scientist

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:
o Prompt engineering and fine-tuning
o Retrieval-Augmented Generation (RAG)
o 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.

Knowledge Base & Documentation
• Build and maintain a shared knowledge base, including:
o Technical recordings and demos
o Code repositories
o Process flow diagrams
• Clearly document end-to-end workflows and system interactions.
• Identify and highlight bottlenecks to support prioritization and continuous improvement.

Cross-functional Collaboration
• Collaborate closely with product, operations, and data teams to understand real-world pain points.
• Translate ambiguous business problems into concrete AI and agent-based solutions.
• Communicate insights, trade-offs, and recommendations clearly to both technical and non-technical stakeholders.

Please reach out to us.