Backend AI/ML Engineer(Strong Python)

Position: Backend AI/ML Engineer(Strong Python) Location- Indore, MP (Hybrid , 3 Days a week) Experience: 3–8 years  Full-time    About the Role:  This role transcends traditional backend development. We’re seeking a highly skilled  Backend AI/ML Engineer with strong Python expertise  and a working understanding of  Full Stack systems.  You’ll architect and scale backend infrastructures that power our  AI-driven products , while also collaborating across f rontend, blockchain, and data science layers  to deliver end-to-end, production-grade solutions. You will engineer the backbone for advanced AI ecosystems — building robust  RAG pipelines, autonomous AI agents, and intelligent, integrated workflows.  Your work will bridge the gap between foundationa l ML models  and scalable, high-performance applications.    Key Responsibilitie s   Architect & Build Scalable AI Systems   ● Design, develop, and deploy high-performance, asynchronous APIs using Python and FastAPI.  ● Ensure scalability, security, and maintainability of backend systems powering AI workflows.   Develop Advanced LLM Workflows    ● Build and manage multi-step AI reasoning frameworks using Langchain and Langgraph for stateful, autonomous agents.  ● Implement context management, caching, and orchestration for efficient LLM performance.   Engineer End-to-End RAG Pipelines  ● Architect full Retrieval-Augmented Generation (RAG) systems — including data ingestion, embedding creation, and semantic search across vector databases such as Pinecone, Qdrant, or Milvus.    Design and Deploy AI Agents   ● Construct autonomous AI agents capable of multi-step planning, tool usage, and complex task execution.   ● Collaborate with data scientists to integrate cutting-edge LLMs into real-world applications.   Workflow Automation & Integration    ● Implement system and process automation using n8n (preferred) or similar platforms.  ● Integrate core AI services with frontend, blockchain, or third-party APIs through event-driven architectures.   Full Stack Collaboration (Good to Have)    ● Contribute to frontend integration and ensure smooth communication between backend microservices and UI layers.   ● Understanding of React, Next.js, or TypeScript is a plus.  ● Collaborate closely with full stack and blockchain teams to align AI services with user-facing applications.  Optimize & Deploy ML Models    ● Serve and maintain a variety of ML models in production.   ● Implement robust monitoring, logging, and testing practices for AI-driven systems.      Required Skills & Qualifications   ●  Expert-level Python  for scalable backend system development.  ● Strong experience with  FastAPI, async programming, and RESTful microservices.   ● Deep hands-on experience with  Langchain and Langgraph for LLM workflow orchestratio n.  ●  Proficiency in Vector Databases ( Pinecone, Qdrant, Milvus) for semantic search and embeddings.   ● Production-level  RAG implementation  experience.  ● Experience integrating  ML models with backend APIs.  ● Strong understanding of containerization (Docker, Kubernetes) and CI/CD workflows.   ● Excellent problem-solving, architecture, and debugging skills     Preferred / Good-to-Have:    ●  Frontend Familiarity : Basic to intermediate knowledge of React.js or similar frameworks for integration testing and full-stack alignment.   ●  Workflow Automation:  Experience with n8n, Airflow, or equivalent orchestration tools.   ●  Blockchain Awareness : Understanding of blockchain integration with AI/ML workflows is a strong plus. (At CCube, Blockchain = Full Stack + AI — cross-functional collaboration is highly valued.)   ●  Broad ML Knowledge : Familiarity with classical ML models (SVM, GBM, Clustering) and deep learning architectures (CNNs, RNNs, Transformers).   ●  Protocol Design:  Experience defining custom communication protocols (e.g., MCP – Model Context Protocol).  ● DevOps/MLOps : Hands-on with AWS / GCP / Azure, pipelines, and model deployment tools.   ●  Data Engineering Basics:  Exposure to ETL pipelines, Kafka/RabbitMQ, or streaming architectures. Powered by JazzHR