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About the role
Job Description : The ideal candidate is a self-motivated, multi-tasker, and demonstrated team-player. You will be a lead developer responsible for the development of new software products and enhancements to existing products. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills. 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. Qualifications : Must-Have Skills : - 7+ years of experience in full stack development. - Strong hands-on experience with FastAPI (or Flask/Django) and Python. - 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. Additional Information : 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). Job Description : The ideal candidate is a self-motivated, multi-tasker, and demonstrated team-player. You will be a lead developer responsible for the development of new software products and enhancements to existing products. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills. 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. Qualifications : Must-Have Skills : - 7+ years of experience in full stack development. - Strong hands-on experience with FastAPI (or Flask/Django) and Python. - 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. Additional Information : 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).
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