Senior Software Engineer

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)