AI Systems Developer

1 day ago

Gandhinagar, Gujarat, India beBeeArtificial Full time ₹ 1,20,00,000 - ₹ 1,80,00,000

We are seeking an experienced AI Developer skilled in applying Large Language Models (LLMs) and building AI-driven applications to join our growing team.

Job Description

A significant part of this role involves designing and developing AI Agents within our platform with an initial focus on integrating external LLM APIs via sophisticated prompt engineering and RAG techniques into these agents, built using Python + FastAPI.

You will architect the logic for these agents, enabling them to perform complex tasks within our e-commerce and retail data orchestration pipelines. Furthermore, as we evolve, this role offers the potential to grow into customizing and deploying LLMs in-house, so adaptability and a strong foundation in ML/LLM principles are key.

Main Responsibilities:
  • Design, develop, test, and maintain the core logic for AI Agents within FastAPI services.
  • Integrate with external LLM provider APIs.
  • Implement and optimize Retrieval-Augmented Generation (RAG) patterns using vector databases to provide relevant context to LLM API calls made by agents.
  • Build and maintain scalable FastAPI microservices that host AI Agent logic and handle interactions with LLMs and other platform components in a containerized environment.
  • Prepare and preprocess data required for effective prompt context, RAG retrieval, and potentially for future fine-tuning tasks.
Required Skills & Qualifications

To excel in this position, you should possess:

  • 4–6 years of hands-on experience in software development with a strong focus on AI/ML application development.
  • Demonstrable experience integrating and utilizing external LLM APIs in applications.
  • Proven experience with Prompt Engineering techniques.
  • Strong Python programming skills.
  • Practical experience building and deploying RESTful APIs using FastAPI.
  • Experience designing and implementing application logic for AI-driven features or agents.
  • Understanding and practical experience with RAG concepts and vector databases.
  • Solid understanding of core Machine Learning concepts and familiarity with frameworks like PyTorch, TensorFlow, or Hugging Face.
  • Familiarity with cloud platforms and containerization for application deployment.
Bonus Points

The following qualifications are highly desirable but not mandatory:

  • Experience with frameworks like LangChain or LlamaIndex.
  • Experience with observability and debugging tools for LLM applications.
  • Experience with graph databases and query languages.
  • Experience with MLOps practices.
  • Knowledge of AI security considerations and bias mitigation.

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