Key Responsibilities :
Design and deploy stateful, multi-agent workflows using LangGraph and LangChain.
Integrate and optimize OpenAI and Google Gemini APIs for task execution, extraction,
and automated reasoning.
Build scalable web automation pipelines using Playwright, Selenium, and Browser Use
to navigate complex web settings and execute browser tasks autonomously.
Clean, transform, and analyze structured and unstructured data using Pandas, NumPy,
and complex SQL queries.
Develop, experiment with, and benchmark AI agents and data scripts inside interactive
Jupyter Notebook environments.
Apply fundamental Deep Learning principles to enhance data extraction, classification,
and model fine-tuning.
Manage source code, branch deployments, and cooperative feature development using
Git and GitHub.
Required Technical Skills
Core Languages:
Deep expertise in Python and advanced relational database querying
in SQL.
Agentic AI & Orchestration: Proven experience building tool-using agents via
LangGraph and LangChain.
LLM Integrations: Production experience working directly with OpenAI (GPT series)
and Gemini APIs.
Browser Automation: Hands-on experience with BrowserUse, Playwright, and
Selenium for scraping, form automation, and session management.
Data Science Toolkit: Mastery of Pandas, NumPy, and Jupyter Notebooks for rapid
prototyping and data pipelines.
Machine Learning: Solid understanding of Deep Learning concepts and architectures.
Version Control: Standard team workflows utilizing Git and GitHub (pull requests,