Generative AI Software Developer

2 days ago

Jodhpur, Rajasthan, India beBeeBackend Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

About us:

We are a software development services firm that creates uncommon solutions for common problems using the right technologies and best practices.

Our team works with startup founders to build minimum viable products and with existing enterprises to help solve interesting problems.

We have established ourselves as industry leaders, with 65+ associates and 40 products built for our clients, 20 of which have either gotten funded/acquired/have become profitable.

We are seeking developers who are hands-on with Generative AI (GenAI), Model Context Protocol (MCP), Agent-to-Agent (A2A) workflows, and Retrieval-Augmented Generation (RAG).

You will architect, implement, and optimize AI backends that combine Python engineering discipline with GenAI capabilities like tool orchestration, retrieval pipelines, and observability.

  • Key Responsibilities
  • Architect and implement AI backends using Python programming language.
  • Develop MCP servers to expose tools, resources, and APIs to Large Language Models.
  • Design and implement multi-agent orchestration.
  • Build pipelines for agents to delegate tasks, exchange structured context, and collaborate.
  • Implement RAG pipelines: text preprocessing, embeddings, chunking strategies, retrieval, re-ranking, and evaluation.
  • Integrate with LLM APIs and open-source models.
  • Required Skills & Qualifications
  • 3–7 years professional experience with Python (version 3.9+).
  • Strong knowledge of object-oriented programming, async programming, and REST API design.
  • Familiarity with MCP concepts and hands-on experience with MCP server implementations.
  • Proficiency with FastAPI/Django for backend development.
  • Comfort with Docker, GitHub Actions, CI/CD pipelines.
  • Nice-to-Have
  • Exposure to AI observability & evaluation.
  • Contributions to open-source AI/ML or MCP projects.
  • Prior work with custom embeddings, fine-tuning, or LLMOps stacks.

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