Backend Developer – AI Platform

Backend Developer – AI Platform at Systems Limited Develop scalable backend services and microservices powering multi-tenant RAG and agentic AI platforms using Python/.NET, FastAPI/Node.js, Azure cloud services, Redis, Cosmos DB, Azure AI Search, and Azure AI Foundry, with a strong focus on API security, real-time communication, observability, reliability, and production-ready AI integrations.Responsibilities:Design, develop, and maintain scalable backend services and microservices for multi-tenant AI and agentic platformsBuild secure, scalable, and reliable multi-tenant APIs using Python/.NET and FastAPI/Node.jsImplement authentication and authorization flows using Microsoft Entra ID and MSALDesign and implement Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, chunking, indexing, and re-rankingIntegrate Azure AI Search to support semantic and vector-based retrieval capabilitiesDevelop session, state, and memory management solutions using RedisImplement real-time communication and event-driven capabilities using Azure Web PubSub and Cosmos DB streamsIntegrate OpenAI and Azure OpenAI models through Azure AI Foundry APIsDevelop robust API security mechanisms, including authentication, authorization, validation, and secure service-to-service communicationImplement telemetry, logging, monitoring, exception handling, and application diagnostics across backend servicesBuild and deploy backend workloads using Azure App Service and Azure FunctionsWork with Cosmos DB to design scalable data storage and retrieval solutions for AI workloadsSecure application secrets, credentials, and configuration using Azure Key VaultDevelop containerized applications and support CI/CD pipelines using GitHub-based workflowsTroubleshoot production issues, perform root cause analysis, and implement reliable fixesCollaborate with AI/ML, frontend, DevOps, QA, and product teams to deliver end-to-end platform capabilitiesOptimize backend services for scalability, performance, reliability, and cost efficiencyFollow software engineering, security, cloud-native, and AI platform development best practicesRequirements:4–8 years of strong hands-on experience in backend software developmentStrong programming experience with Python and/or .NETHands-on experience with FastAPI and/or Node.js for backend API developmentStrong understanding of RESTful API design, microservices architecture, and distributed systemsExperience building multi-tenant applications and implementing tenant isolation and access controlStrong experience with authentication and authorization using Microsoft Entra ID and MSALPractical experience implementing Retrieval-Augmented Generation (RAG) solutions and AI-powered backend servicesStrong understanding of RAG concepts including embeddings, document chunking, vector search, retrieval, and re-rankingHands-on experience with Azure AI Search and vector/semantic search capabilitiesExperience integrating OpenAI or Azure OpenAI models through Azure AI FoundryStrong experience with Redis for caching, session management, state management, or conversational memoryExperience implementing real-time communication using Web PubSub, WebSockets, or similar technologiesExperience working with Cosmos DB and event/stream-based data processingHands-on experience with Azure services such as App Service, Functions, Cosmos DB, Redis, Web PubSub, and Key VaultStrong understanding of API security, secure configuration management, error handling, and input validationExperience with application telemetry, logging, monitoring, and observabilityExperience with containerization and deployment of backend servicesStrong understanding of CI/CD pipelines and GitHub-based development workflowsExperience with Git, branching strategies, pull requests, and collaborative software developmentStrong troubleshooting, problem-solving, and debugging skillsAbility to work effectively in a fast-paced environment and collaborate with cross-functional technical teamsExperience building production-grade AI platforms, agentic applications, or LLM-powered solutions is highly preferred