Suparna M.
Backend Developer/AIEngineer/Python/AgenticAI/MultiTenant SAAS/LLM/RAG
๐๐๐๐๐๐ ๐๐๐๐๐๐๐ & ๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐, ๐๐๐๐, ๐๐๐, ๐๐๐๐๐๐๐ ๐๐, ๐๐๐ ๐๐๐๐๐-๐๐๐๐๐๐ ๐๐๐๐. I build production-ready AI-powered backend systems and scalable SaaS platforms that combine Python, LLMs, RAG, AI agents, automation, APIs, and secure multi-tenant architectures. My focus is on turning complex business requirements into reliable AI products from intelligent assistants and knowledge systems to CRM automation, autonomous agents, enterprise workflows, and scalable SaaS platforms. ๐๐๐๐ ๐ ๐๐๐๐: AI Agents โข LLMs โข RAG โข Python โข FastAPI โข Multi-Tenant SaaS โข CRM โข AI Automation โข PostgreSQL โข Redis โข Vector Databases โข AWS ๐๐๐๐ ๐ ๐๐๐ ๐๐๐๐ ๐๐๐ ๐๐๐๐๐? โธ ๐๐ ๐๐๐๐๐๐ & ๐๐๐๐๐๐๐ ๐๐ โ Production-grade AI agents for real business workflows. โ LangGraph, LangChain, CrewAI, AutoGen, and custom orchestration. โ Tool calling, function calling, memory, planning, routing, and workflows. โ AI agents connected to APIs, CRMs, databases, and business systems. โ Human-in-the-loop and approval-based automation. โ Multi-agent systems for sales, support, research, and operations. โธ ๐๐๐ / ๐๐๐๐๐๐๐๐๐๐ ๐๐ โ OpenAI, Anthropic Claude, Gemini, and open-source LLMs. โ LLM application architecture and model integration. โ Prompt engineering and structured outputs. โ Context management, memory, and conversational AI. โ Model selection, cost optimization, latency optimization, and reliability. โ Ollama and vLLM for self-hosted AI solutions. โธ ๐๐๐ & ๐๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐ โ Production-ready RAG pipelines for private and enterprise data. โ Document ingestion, chunking, embeddings, indexing, and retrieval. โ Semantic search, hybrid search, metadata filtering, and reranking. โ Pinecone, Qdrant, Weaviate, pgvector, and MongoDB Atlas Vector Search. โ Elasticsearch and AWS OpenSearch. โ AI knowledge bases for internal teams, customers, and enterprise applications. โ Retrieval optimization, evaluation, and hallucination reduction. โธ ๐๐๐๐๐-๐๐๐๐๐๐ ๐๐๐๐ โ Scalable SaaS platforms supporting multiple organizations. โ Secure tenant isolation and organization-level data management. โ RBAC, permissions, authentication, and user management. โ Multi-tenant PostgreSQL architecture. โ Subscription and usage-based SaaS models. โ Tenant-specific AI assistants, knowledge bases, workflows, and configurations. โ Production-ready APIs and backend services. โธ ๐๐-๐๐๐๐๐๐๐ ๐๐๐ & ๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐ โ AI-powered lead qualification and enrichment. โ Sales pipeline and opportunity management. โ Automated follow-ups and customer engagement. โ AI sales assistants and customer support agents. โ AI-powered quotations, proposals, summaries, and recommendations. โ CRM, ERP, database, and third-party API integrations. โ n8n, Make, Zapier, and custom Python automation. โธ ๐๐๐ & ๐๐ ๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐ โ Custom MCP servers and tools. โ Connecting AI agents with APIs, databases, CRMs, and internal systems. โ Custom tool ecosystems for AI assistants. โ Enterprise AI integrations and autonomous workflows. โธ ๐๐๐๐๐ / ๐๐๐๐๐๐ / ๐๐๐๐๐๐๐๐๐๐ โ AWS: S3, SQS, Lambda, DynamoDB, EKS, Kinesis, Bedrock, CloudFront. โ Docker, Kubernetes, Helm, ArgoCD, and Terraform. โ CI/CD and automated deployment pipelines. โ Datadog, OpenTelemetry, and Sentry. โ Scalable cloud infrastructure for AI and SaaS workloads. ๐๐๐ ๐๐๐๐ ๐๐๐๐ ๐๐? I don't just connect an LLM to an application. I engineer the complete AI backend around your business including LLM strategy, RAG architecture, agent orchestration, APIs, databases, tenant isolation, automation, evaluation, observability, and production infrastructure. ๐ ๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐๐ ๐๐๐๐ ๐๐๐ ๐๐๐๐๐๐๐๐, ๐๐๐๐๐๐, ๐๐๐๐๐๐๐๐, ๐๐๐ ๐๐๐๐๐ ๐ ๐๐ ๐๐๐๐๐๐๐๐๐๐.