Key Responsibilities Build and deploy enterprise-grade Generative AI and ML solutions Design scalable AI systems enabling natural language–driven automation and insights Develop and implement GenAI workflows for enterprise use cases Build LLM-powered applications for:

Analytics & reporting Document intelligence Recommendation systems Design and implement advanced RAG (Retrieval-Augmented Generation) pipelines including:

Embeddings Vector search Ranking and grounding mechanisms Build and expose AI capabilities via REST APIs and microservices Deploy, monitor, and manage solutions using Docker and cloud platforms Implement output validation, monitoring, and evaluation frameworks for production reliability Required Skills Experience with Programming (Python, SQL, NoSQL, Spark) and ML tools and cloud technologies (AWS, Azure, GCP).

Deep understanding of ML algorithms for common use cases in both structured and unstructured data systems.





Experience with GenAL/ LLM tools: LangChain, RAG pipelines, Embeddings & vector databases, Multi-modal LLMs, Fine-tuning techniques Experience in building FastAPI-based services and Dockerized deployments Experience building production-grade GenAI solutions Familiarity with:

Multi-agent architectures and orchestration Exposure to enterprise analytics / BI tools:

Power BI, Tableau, or other visualization tools Experience collaborating with UI/UX teams for AI-driven solution delivery Preferred Qualifications Experience in designing scalable AI architectures for enterprise environments Robust understanding of AI system evaluation, monitoring, and guardrails * Ability to translate business problems into AI-driven solutions

📌 Data Scientist (Noida)
🏢 EXL
📍 Noida