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, , 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 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.