About the Role

We are looking for a strong AI Engineer / Data Scientist / Generative AI Engineer to build intelligent AI-powered applications for the financial services domain. The role involves working across NLP, LLMs, RAG, semantic search, machine learning, and production-grade AI application development.

The ideal candidate should be a strong hands-on individual contributor with excellent Python and backend development skills and experience taking AI solutions from development to production.

Key Responsibilities

- Design and develop intelligent AI/ML and Generative AI applications using NLP and LLM techniques to solve real-world business problems.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured data.
- Integrate and orchestrate LLMs/SLMs for question answering, summarization, semantic search, and document understanding.
- Develop and maintain RESTful APIs, including synchronous and asynchronous APIs, using FastAPI, Flask, or similar frameworks.
- Apply advanced prompt engineering and prompting techniques to improve LLM performance.
- Build semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases such as FAISS, Pinecone, or Weaviate.
- Develop NLP solutions involving NER, text classification, intent detection, embeddings, sentiment analysis, and document understanding.
- Build, train, and evaluate Machine Learning and Deep Learning models for NLP and structured data use cases.
- Monitor, evaluate, and optimize LLM/SLM performance using real-world data to improve accuracy, relevance, latency,



and reliability.
- Work with LLMOps/MLOps tools for model monitoring, evaluation, experimentation, and versioning.
- Develop traditional ML models for structured data analysis and predictive use cases.
- Collaborate with cross-functional teams to identify system issues, business opportunities, and areas for improvement.
- Participate in solution design and implementation across new and existing projects.
- Work independently as an Individual Contributor, taking ownership of assigned projects and deliverables.

Mandatory Requirements

- 3+ years of hands-on experience in Data Science, AI, ML, Deep Learning, NLP, or Generative AI application development.
- Strong hands-on experience in Python programming, backend development, API development, and production-grade application support.
- Experience with ML/DL frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.
- Hands-on experience with NLP use cases such as text classification, sentiment analysis, NER, semantic search, embeddings, or document understanding.
- Solid experience working with LLMs such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.
- Hands-on experience building or implementing RAG solutions,



vector search, semantic search, or knowledge-based AI applications.
- Strong experience in Prompt Engineering and Generative AI frameworks/technologies such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar.
- Experience developing, consuming, or integrating APIs using FastAPI, Flask, or similar Python frameworks.
- Strong ability to work as an independent contributor with a problem-solving mindset.
- Age: Candidate should be below 28 years.
- Education: B.Tech/M.Tech from Tier 1 institutions, including IITs, NITs, BITS, IIITs, DTU, or NSUT.

Preferred Qualifications

- Experience with LLMOps/MLOps tools for monitoring, evaluation, experimentation, and model versioning.
- Exposure to Azure OpenAI, Azure Kubernetes Service (AKS), Kubernetes, cloud-native AI deployments, or distributed systems.
- Experience with PostgreSQL, MongoDB, Redis, Kafka, or large-scale data platforms.
- Familiarity with Docker, Kubernetes, cloud platforms, and scalable deployment architectures.
- Experience working with AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.

Compensation The compensation structure will be 75% Fixed + 25% Variable, as per company policy.

Ideal Candidate The ideal candidate is a hands-on AI/ML engineer with strong Python, NLP, LLM, RAG, and backend development expertise, who can independently build and deploy production-grade Generative AI solutions and contribute across the complete AI application lifecycle.

📌 Data Scientist / AI Engineer (Python, ML, RAG) (Maharashtra)
🏢 Bajaj FinServ
📍 Maharashtra