NielsenIQ

Senior Engineer with Python, GenAI & Database systems

NielsenIQ
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7 hours ago
Pune, IndiaSenior

Responsibilities

  • Build scalable, production-grade AI systems involving large-data queries.
  • Develop MCP-based agentic AI chatbots with intent classification and agent state management.
  • Build scalable APIs with FastAPI and integrate LLM APIs from providers such as OpenAI, Claude, and Azure OpenAI.
  • Manage structured and unstructured data in MongoDB, including schema design and aggregation pipelines.
  • Collaborate with AI engineers to productionize GenAI use cases including chatbots, summarization, classification, and embedding search.
  • Design token-efficient LLM API interactions and manage provider rate limits.
  • Optimize the performance, latency, and reliability of AI-enhanced APIs.
  • Maintain clean, secure, and testable backend and frontend code.
  • Own end-to-end features spanning user experience, backend logic, and 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, OpenAI LLMs, multi-agent AI systems, and MCP-based AI architectures.
  • Solid experience with MongoDB, including schema design and aggregation pipelines.
  • Experience integrating LLM APIs such as OpenAI, Anthropic, Cohere, Mistral, and Azure OpenAI.
  • Deep understanding of RESTful API design and best practices.
  • Experience with Git, Docker, and CI/CD pipelines.
  • Familiarity with prompt engineering, embeddings, and vector databases such as Pinecone, FAISS, and Weaviate is preferred.
  • Angular knowledge and experience building GenAI-driven interfaces are preferred.
  • Knowledge of JWT, OAuth2, API rate-limiting strategies, LLM token usage, context-length constraints, and caching is preferred.
  • Experience with PostgreSQL or hybrid MongoDB/PostgreSQL data models is preferred.
  • DevOps awareness and experience with Kubernetes or cloud deployment on AWS, Azure, or GCP are preferred.

Benefits

  • Flexible working environment.
  • Volunteer time off.
  • LinkedIn Learning.
  • Employee Assistance Program (EAP).
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