Description About The Role Our client is looking for a passionate and motivated Junior Generative AI Engineer who has 0–2 years of experience (or strong project/internship exposure) in building AI/LLM-based applications. This role is ideal for candidates who have good foundational knowledge of Generative AI, LLMs, and backend development—and want to grow into a full-stack AI engineer over time. You will work with senior engineers and contribute to building chatbots, automation tools, RAG systems, and LLM-powered apps that solve real-world business problems. This role gives you exposure to modern AI tools, mentorship, and hands-on experience with enterprise-grade AI applications. Key Responsibilities Assist in building AI/LLM-based applications such as chatbots, copilots, content generators, and workflow automation tools. Support the development and enhancement of RAG pipelines, embeddings, and vector search systems. Work on integrating AI models with backend systems using Python (FastAPI/Flask) or Node.js . Help implement prompt engineering, model evaluation, and fine-tuning tasks under senior guidance. Develop API endpoints and backend services required for AI model orchestration. Contribute to testing, validating, and optimizing AI outputs to reduce hallucinations and improve reliability. Collaborate with product, engineering, and data teams to understand requirements and deliver solutions. Stay updated with the latest AI tools, models, and frameworks to continuously improve your skill set. Required Skills 0–2 years of experience in AI/ML, Generative AI, NLP, or software development (internships, projects, freelance work, or academic work also counts). Strong foundational knowledge of Python and basics of web frameworks (FastAPI/Flask). Basic understanding of LLMs, embeddings, vector databases (Pinecone, FAISS, Chroma, or similar). Familiarity with prompt engineering and working with APIs like OpenAI, HuggingFace, Cohere, etc. Good understanding of backend and API development fundamentals. Knowledge of Git, version control, and collaborative development practices. Curiosity and willingness to learn modern AI tech stacks like LangChain, LlamaIndex, or LangGraph. Preferred Skills (Good to Have) Experience with any Generative AI project (college project, hackathon, internship). Basic understanding of RAG concepts and vector search. Exposure to Docker, cloud platforms (AWS/GCP/Azure), or MLOps concepts. Familiarity with multimodal AI (image, audio, video). Knowledge of fine-tuning techniques like LoRA/QLoRA (even theoretical understanding is fine). Soft Skills Strong problem-solving ability with a willingness to experiment and iterate. Good communication skills to explain ideas clearly. Growth mindset and eagerness to learn from senior engineers. Ability to work in a fast-paced, dynamic environment. Team player attitude with a proactive approach.