Description :

About the Role :

We are looking for an experienced Data Science Manager with strong expertise in Python programming, Generative AI, and Large Language Models (LLMs) to design and develop advanced AI solutions. The ideal candidate will have hands-on experience with RAG (Retrieval-Augmented Generation) architecture, LangChain, LangGraph, and end-to-end model deployment.

You will work closely with cross-functional teams (AI Engineering, Data Engineering, Product, and Research) to build intelligent systems, automate workflows, and drive innovation through GenAI-based solutions.

Key Responsibilities :

- Design, develop, and deploy Generative AI and LLM-based applications using frameworks such as LangChain, LangGraph, and RAG techniques.

- Write efficient and scalable Python code for data processing, model training, and inference pipelines.

- Implement custom LLM workflows, prompt engineering, and fine-tuning strategies for domain-specific use cases.

- Integrate vector databases (e.g., FAISS, Pinecone, ChromaDB, Weaviate) for retrieval and semantic search solutions.

- Collaborate with data engineers to build and maintain data pipelines, ensuring data quality and integrity.

- Perform data analysis, feature engineering, and statistical modeling to extract insights and improve model performance.

- Work with cloud environments (AWS, Azure, GCP) to deploy and scale AI solutions.

- Stay current with the latest trends in GenAI, LLMs, and AI frameworks, and apply them to business problems.

Required Skills and Experience :

- 8 to 12 years of total experience in Data Science, Machine Learning, or AI development.

- Strong proficiency in Python and popular data science libraries (NumPy, pandas, scikit-learn, PyTorch, TensorFlow).

- Hands-on experience with Generative AI frameworks such as LangChain, LangGraph, LLM APIs (OpenAI, Anthropic, etc.), and RAG architectures.

- Expertise in prompt engineering, vector search, and document retrieval techniques.

- Experience deploying and managing LLM-based solutions in production environments.

- Knowledge of MLOps, model evaluation, and experiment tracking tools (e.g., MLflow, DVC, Weights & Biases).

- Familiarity with cloud-based AI services (AWS Sagemaker, Azure OpenAI, GCP Vertex AI).

- Excellent problem-solving, communication, and collaboration skills.

Preferred / Nice-to-Have :

- Experience with Graph-based reasoning and workflow orchestration tools (LangGraph, LlamaIndex, etc.).

- Background in Natural Language Processing (NLP) and transformer-based models.

- Exposure to API integration, microservices, and containerization (Docker, Kubernetes).

- Prior experience mentoring junior data scientists or leading AI projects.

Education :

- Bachelors or masters degree in computer science, Data Science, AI/ML, Statistics, or a related field.