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
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:
- Exposure to:
- Real-world GenAI applications