Backend AI/ML Engineer

3 hours ago

Indore Madhya Pradesh India, Madhya Pradesh TalentLynk Full time

Position: Backend AI/ML Engineer (with Full Stack Expertise)

Experience: 3–8

Type: Fulltime| 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

  • Design, develop, and deploy high-performance, asynchronous APIs using Python and FastAPI.
  • Ensure scalability, security, and maintainability of backend systems powering AI 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.
  • Architect full Retrieval-Augmented Generation (RAG) systems — including data ingestion, embedding creation, and semantic search across vector databases such as Pinecone, Qdrant, or Milvus.
  • 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.
  • 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.


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

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