Back End Developer

0 years

0 Lacs

Posted:8 hours ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About the Role

Backend Developer (AI/ML Integration)

You will design scalable backend services, integrate AI models (including LLMs such as GPT-5), develop APIs, and deploy intelligent microservices powering automation, analytics, and enterprise knowledge platforms.

Key Responsibilities

Backend Engineering & API Development

  • Design, develop, and maintain scalable backend services and RESTful APIs.
  • Build microservice-based solutions ensuring performance, reliability, and scalability.
  • Participate in code reviews, debugging, and production performance tuning.

AI/ML & LLM Integration

  • Integrate AI/ML and LLM models (e.g., GPT-5, fine-tuned/custom models) into backend workflows.
  • Develop and deploy ML/NLP models for automation, predictive analytics, and intelligent knowledge retrieval.
  • Customize and optimize AI plugins for automation, analytics, and insights.

ML Pipelines & MLOps

  • Build and maintain end-to-end ML pipelines for training, testing, and deployment.
  • Use MLOps tools (MLflow, Kubeflow, DVC) for experiment tracking and model lifecycle management.
  • Work with vector databases (Pinecone, Weaviate, FAISS, Milvus) to build AI-driven search/retrieval systems.

Cloud, DevOps & Automation

  • Work with cloud platforms (AWS, Azure, GCP) for deployment and infrastructure management.
  • Implement CI/CD pipelines for automated deployment and monitoring.
  • Use automation/orchestration tools like Airflow or Prefect for workflow automation.
  • Work with containerization & orchestration tools (Docker, Kubernetes).
  • Ensure data security, compliance, and scalability across all deployments.

Required Skills & Qualifications

Core Technical Skills

  • Strong programming expertise in

    Java

    and

    Python

    .
  • Excellent understanding of

    data structures, algorithms, and software design principles

    .
  • Hands-on experience with

    AI/ML frameworks

    : TensorFlow, PyTorch, Hugging Face.
  • Proficiency in

    NLP/LLM integration

    , including LangChain, RAG, OpenAI APIs, and Anthropic models.
  • Experience with backend frameworks and

    microservice architectures

    .

Cloud & DevOps

  • Familiarity with

    AWS

    cloud infrastructure and Terraform (IaC).
  • Working knowledge of Docker, Kubernetes, and CI/CD workflows.

AI Infrastructure

  • Experience with

    vector databases

    (Pinecone, Weaviate, FAISS, Milvus).
  • Understanding of MLOps tools such as MLflow, Kubeflow, or DVC.

Nice to Have

  • Internship or project experience in AI/LLM integration or backend automation.
  • Experience with API security, authentication, and scalable system architecture.
  • Exposure to RAG frameworks and chatbot tools: Rasa, Dialogflow, Botpress.
  • Contributions to open-source AI/automation projects.

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