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Senior Software Engineer, Pune
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
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
Nice to Have:
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)
Employment type
Full-time
Work arrangement
Hybrid
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