Senior GenAI Data Scientist / AI Engineer (LLM, RAG, Agentic AI)

Job Summary

We are seeking a highly skilled GenAI Data Scientist / AI Engineer with strong expertise in Machine Learning, Generative AI, and Agentic AI systems.

The ideal candidate will design, build, and deploy scalable AI/ML and GenAI solutions, including LLM-based applications, RAG pipelines, and intelligent AI agents, while ensuring performance, scalability, and business impact.

Key Responsibilities

Machine Learning & Data Science

• Design, build, and deploy ML models using:
  • XGBoost, LightGBM, Scikit-learn
• Perform:
  • Model training, validation, and optimization
• Translate business problems into data-driven solutions

Generative AI & Agentic AI

• Design and implement:
  • LLM-based applications
  • AI agents and workflows
• Work with frameworks like:
  • LangChain / LangGraph / CrewAI / AutoGen
• Enable:
  • Tool calling
  • Task automation
  • Multi-agent orchestration

RAG & Knowledge Systems

• Build Retrieval-Augmented Generation (RAG) pipelines
• Work with:
  • Vector databases
  • Embeddings
• Develop knowledge-based AI systems

Model Deployment & MLOps

• Deploy models into production environments
• Implement:
  • CI/CD pipelines
  • MLflow / model monitoring
• Ensure:
  • Model performance
  • Scalability
  • Reliability

Cloud & Data Engineering

• Work on cloud platforms:
  • AWS / Google Cloud Platform
• Build scalable data pipelines and ML workflows

Monitoring & Optimization

• Monitor:
  • Model performance
  • Data drift
• Continuously improve models and pipelines

Security & Compliance

• Ensure:
  • Data security
  • Compliance standards
• Implement governance for AI systems

Collaboration & Communication

• Engage with:
  • Business stakeholders
  • Engineering teams
• Translate business requirements into AI solutions
• Communicate model insights clearly

Required Skills

Machine Learning (MANDATORY)

• Strong experience with:
  • XGBoost
  • LightGBM
  • Scikit-learn

Programming

• Python (mandatory)

Generative AI

• LLMs (GPT, Claude, etc.)
• Prompt engineering
• AI agents / Agentic workflows

RAG Systems

• Vector databases
• Embeddings
• Retrieval pipelines

MLOps & Deployment

• Model deployment
• CI/CD pipelines
• MLflow / monitoring tools

Cloud Platforms

• AWS / Google Cloud Platform

Statistics & Analytics

• Strong statistical modeling
• Data analysis and interpretation

Experience Required

• 8+ years of experience in:
  • Data Science / Machine Learning
• Hands-on experience in:
  • Generative AI (intermediate level)

Preferred Skills

• Experience with:
  • LangChain / CrewAI / AutoGen
  • Vector DBs (Pinecone, FAISS, etc.)
• Experience in:
  • Agentic AI systems
• Exposure to:
  • Real-world GenAI applications