# Data Scientist (AI / GenAI)
## Job Summary
The Data Scientist (AI / GenAI) will play a pivotal role in designing, developing, deploying, and optimizing next-generation AI-powered enterprise products. The focus is on leveraging advanced Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems to create scalable, reliable, and innovative solutions across various domains such as Tax Technology, Compliance, Financial Services, and Enterprise Intelligence. The candidate will collaborate closely with Product, Engineering, and Business teams to translate complex business problems into cutting-edge AI applications that deliver tangible value.
## Responsibilities
- Design, build, and deploy **production-grade AI and Machine Learning solutions** tailored to enterprise needs.
- Develop and optimize **LLM-powered applications**, including RAG, GraphRAG, Agentic AI, and multimodal systems.
- Fine-tune and customize **Large Language Models** using techniques such as LoRA, PEFT, and transfer learning.
- Build intelligent systems such as **chatbots, search engines, recommendation engines, and knowledge retrieval systems**.
- Design and optimize **prompt engineering frameworks** for various business use cases.
- Develop scalable **AI pipelines, model-serving frameworks, and API-based AI services**.
- Work with structured and unstructured data to create **predictive and generative AI solutions**.
- Collaborate with cross-functional teams to **translate business problems into AI-driven solutions**.
- Evaluate emerging AI technologies, models, frameworks, and tools, and recommend their applicability.
- Ensure deployed models are **scalable, reliable, secure, and production-ready**.
## Qualifications
- **Technical Skills:**
- Generative AI (Mandatory)
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- GraphRAG
- Prompt Engineering
- AI Agents and Agentic Workflows
- LLM Fine-Tuning (LoRA, PEFT)
- Embeddings & Vector Search
- Multimodal AI Applications
- Frameworks & Tools: Python, LangChain, LangGraph, Neo4j, Graph Databases, Vector Databases (Pinecone, ChromaDB, Weaviate, PgVector or equivalent)
- Machine Learning: Classification, Regression, Ensemble Learning, Feature Engineering, Model Evaluation & Optimization
- Application Development: FastAPI, REST APIs, Model Deployment, API-Based AI Services
- Data & Databases: SQL, PostgreSQL, Neo4j, Vector Databases, Knowledge Graphs
- **Educational Qualifications:**
- Relevant degree in Computer Science, Data Science, AI, or related fields (BTech, BSc, MSc, or higher)
## Preferred Skills
- Experience with **Agentic AI** and related frameworks (MCP, Google ADK, AutoGen, CrewAI, Semantic Kernel)
- Familiarity with **Multi-Agent Architectures**
- Exposure to **cloud platforms** such as AWS, Azure, or GCP
- Knowledge of **MLOps and CI/CD pipelines**
- Experience with **Finetuning open-source LLMs**
- Knowledge of **Model Monitoring and Evaluation Frameworks**
- Experience building **Agentic AI systems**
- Familiarity with **financial services, compliance, tax technology, or enterprise SaaS products**
## Experience
- **3-6 years** of experience as a Data Scientist, AI Engineer, Machine Learning Engineer, or similar role.
- Proven hands-on experience in **building and deploying production-grade AI applications** used by customers or internal users.
- Demonstrated expertise in **LLMs, RAG, LangChain, Python, Machine Learning, and Knowledge Graphs**.
- Experience integrating AI solutions into **enterprise applications**.
- Ability to independently own AI initiatives from **problem definition to deployment**, handling challenges related to **performance, scalability, reliability, and monitoring**.
## Environment
- The role involves working in a **collaborative, fast-paced environment** with a focus on **enterprise AI solutions**.