Senior Engineer with Python, GenAI & Database systems at NielsenIQ in Pune, MH, India

Job description

• We're building the next generation of intelligent applications powered by LLMs and GenAI. Join our AI product team as a GenAI Engineer where you’ll architect and implement APIs using FastAPI, create engaging frontends with Angular, and work with MongoDB as the primary data store. Your code will directly power AI experiences for real users.

Responsibilities

• Build scalable and production grade AI systems involving big data queries.
• Build MCP based Agentic AI chat bot dealing with intent classification, agent state management, etc.
• Build scalable REST APIs in FastAPI to integrate with LLM APIs (OpenAI, Claude, Azure OpenAI, etc.)
• Manage and query structured/unstructured data in MongoDB
• Work closely with AI engineers to productionize GenAI use cases (chatbots, summarization, classification, embedding search)
• Design token-efficient API interactions and manage rate limits with LLM providers
• Optimize performance, latency, and reliability of AI-enhanced APIs
• Maintain clean, secure, and testable code across backend and frontend
• Own end-to-end features: from UX to backend logic to API integration

Requirements

• 5+ years of experience in full stack development
• Strong hands-on experience with FastAPI (or Flask/Django) and Python 3.x
• Strong hands-on experience with LangChain, LangGraph, Agentic AI and openAI LLM.
• Strong hands-on experience with Multi Agentic AI systems.
• Strong hands-on experience with MCP based AI architectures.
• Solid experience with MongoDB (including schema design and aggregation pipelines)
• Experience integrating with LLM APIs (e.g. OpenAI, Anthropic, Cohere, Mistral, Azure OpenAI, etc.)
• Deep understanding of RESTful API design and best practices
• Git, Docker, and familiarity with CI/CD pipelines
• Familiarity with prompt engineering, embeddings, vector databases (like Pinecone, FAISS, Weaviate)
• UI/ Angular knowledge.
• Experience working on GenAI-driven UIs (chat interfaces, knowledge panels, QCA)
• Knowledge of JWT, OAuth2, API rate limiting strategies
• Basic understanding of LLM token usage, context length constraints, and caching
• Experience with PostgreSQL or hybrid Mongo/Postgres data models
• DevOps awareness: Kubernetes, cloud deployment (AWS/Azure/GCP)

Skills

Required

• Python 3.x
• FastAPI (or Flask/Django)
• LangChain
• LangGraph
• Agentic AI
• OpenAI LLM
• Multi Agentic AI systems
• MCP based AI architectures
• RESTful API design
• Git
• Docker
• CI/CD pipelines

Preferred

• Prompt engineering
• Embeddings
• Angular
• GenAI-driven UIs
• JWT
• OAuth2
• API rate limiting strategies
• LLM token usage

Benefits

• Our Benefits
• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)