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.