Role Overview

We are seeking an AI Backend Developer to design and build scalable backend systems powered by Large Language Models (LLMs). You will work on AI-driven APIs, Retrieval-Augmented Generation (RAG) systems, AI agents, vector search infrastructure, and intelligent automation workflows using Python and modern AI tooling.

Responsibilities

Develop LLM-powered REST APIs using Python and FastAPI
Build and maintain RAG pipelines using PostgreSQL (pgvector)
Design and optimize prompts for structured, reliable outputs
Build AI agents and multi-step workflows using LangChain/LangGraph
Integrate OpenAI or other LLM providers (streaming, tool calling, structured outputs)
Implement request validation, middleware, authentication, and error handling
Design efficient database schemas and optimize vector similarity queries
Handle document ingestion, embeddings, chunking, and search indexing
Build background processing pipelines for AI tasks and document processing
Ensure performance, scalability, cost-efficiency, and security of AI services
Collaborate with frontend, DevOps, and product teams

Requirements

Strong proficiency in Python
Experience with FastAPI architecture
Hands-on experience with LLM APIs and prompt engineering
Experience with LangChain and AI agent frameworks
Understanding of RAG architecture and vector databases
PostgreSQL with pgvector
REST API design and validation (Pydantic, etc.)
Solid understanding of async programming in Python
Experience building AI-powered applications or agentic workflows

Good to Have

LangGraph or multi-agent orchestration frameworks
Redis (caching, pub/sub, memory)
Background jobs / queues (Celery, RQ, BullMQ alternatives)
File handling (PDF parsing, OCR pipelines)
Docker and cloud deployment knowledge
Authentication & authorization (JWT, OAuth)
Knowledge of observability and LLM evaluation tools

Experience

1–4 years of backend development experience
Hands-on experience building