Gen. AI Developer (Python+AI)

Info Origin Inc.
Gondia, Maharashtra, India

""Immediate to 30 days Joiners Required""

Gen. AI Developer (Python+AI)

Location: Gondia

Experience: 1 to 3 years

Job Type - Full-Time

Interview Type - Video

About the Role

As Gen. AI Developer, you will work in a collaborative, learning-focused environment and gain hands-on experience in building AI powered applications using Python, APIs, Large Language Models, RAG, AI agents and modern AI frameworks.

Key Responsibilities

  • Develop and test AI-powered applications using Python.
  • Build and integrate REST APIs, databases, AI models and external services.
  • Assist in developing LLM, RAG and AI-agent-based solutions.
  • Process structured and unstructured data.
  • Write clean, maintainable, and well-documented code.
  • Debug applications and improve performance and reliability.
  • Participate in code reviews, technical discussions, and project work.

Eligibility

  • B.E., B.Tech., MCA, M.Sc. or equivalent qualification in Computer Science, IT, AI, Data Science, or a related discipline.
  • Available to work on-site.
  • Strong interest in software development and Artificial Intelligence.

Must-Have Skills

  • Python programming and Object-Oriented Programming.
  • Data Structures, Algorithms, and problem-solving fundamentals.
  • SQL and relational database basics.
  • Source Code Management tools (Git/GitHub/Bitbucket) basics.
  • REST API, knowledge of NumPy and Pandas.
  • Machine Learning fundamentals including classification, regression, training and validation, overfitting and evaluation metrics.
  • Understanding of Generative AI and Large Language Models.
  • Good communication, teamwork and learning ability.

Good-to-Have Skills

  • FastAPI, Flask, Django or similar frameworks.
  • Prompt engineering, RAG, AI agents, A2A, MCP.
  • LangChain, LlamaIndex, Semantic Kernel or similar frameworks.
  • Vector databases such as FAISS, Chroma, Pinecone, or Qdrant.
  • Hugging Face models or OpenAI-compatible APIs.
  • Embeddings, transformers, and semantic search.
  • scikit-learn, PyTorch, or TensorFlow.
  • Docker, Linux, cloud fundamentals.
  • Academic, personal, internship or open-source AI projects.

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