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 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 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.