Gen. AI Developer Trainee (Dehradun)

NEW OPPORTUNITY || IMMEDIATE JOINERS REQUIRED - Freshers 2026 Pass Outs Are Welcomed || Position Title:- Gen. AI Developer Trainee Experience:- Freshers Location:- Dehradun, UK (Onsite) About the Role We are looking for enthusiastic 2026 graduates with strong Python fundamentals and interest in Generative AI. As Gen. AI Developer Trainee, 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. - Graduating in 2026. - 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. - Basic understanding of Generative AI and Large Language Models. - Good communication, teamwork and learning ability. Positive-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. Candidates are not expected to know every technology listed above. Strong programming fundamentals, curiosity, problem-solving ability and learning potential will be given greater importance. Learning and Career Growth Selected candidates will receive mentorship, structured learning, hands-on project experience and exposure to modern AI engineering practices. High-performing trainees may be considered for full-time employment based on performance, project completion, business requirements and organizational policies. .