Back End Developer

Technical Requirements
3+ years of professional backend engineering experience.
Strong proficiency in Node.js and TypeScript.
Experience building scalable backend services, REST APIs, and microservices.
Strong understanding of distributed systems, including asynchronous processing, message queues, concurrency, fault tolerance, and service communication.
Hands-on experience implementing Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, embeddings, retrieval, and context management.
Production experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or pgvector.
Hands-on experience building AI agents and agent orchestration workflows, including tool/function calling, multi-step execution, state management, and failure recovery.
Experience integrating LLM APIs, including OpenAI, Anthropic Claude, Gemini, or equivalent providers.
Strong knowledge of PostgreSQL, Redis, database optimization, and caching.
Experience with AWS, GCP, or Azure.
Understanding of authentication, authorization, API security, and secure data handling.
Experience deploying, monitoring, and maintaining production backend systems.
Good to Have
Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
Experience building multi-agent systems.
Familiarity with MCP (Model Context Protocol).
Experience implementing hybrid search, reranking, and retrieval evaluation.
Experience with multi-tenant SaaS architectures.
Familiarity with Docker, Kubernetes, and CI/CD pipelines.
Experience optimizing LLM token usage, latency, and inference costs.
Important
We are specifically looking for engineers who have built and deployed AI-powered backend systems, not candidates whose experience is limited to basic chatbot implementations, tutorials, or proof-of-concept projects.
Candidates should be able to explain their contributions to production RAG pipelines, vector search infrastructure, agent orchestration, and distributed backend architecture.

Work arrangement
No