Position : Backend AI / ML Engineer (with Full Stack Expertise)
Experience : 3–8 years Type : Full-time | Hybrid 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
frontend, 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 foundational ML models and scalable, high-performance applications. Key Responsibilities
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 orchestration.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 skillsPreferred / 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.Skills Required
Docker, FastAPI, react.js , Kubernetes, Python