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Job Title: Junior AI EngineerLocation: Onsite | Full-TimeIndustry: Artificial Intelligence / Software DevelopmentExperience: 1–2 yearsAbout the RoleOur client is a fast-growing technology company building AI-powered products for enterprise customers across industries. They are looking for a passionate AI Engineer to join their team and work on developing, deploying, and optimizing AI-driven solutions that solve real-world business problems.Role OverviewAs an AI Engineer, you will work on building and integrating machine learning and Generative AI solutions into scalable applications. You will collaborate with product managers, data engineers, and backend developers to design intelligent systems that enhance automation, decision-making, and user experience.This role is ideal for someone with 1–2 years of hands-on experience in AI/ML development and a strong interest in building production-ready AI systems.Key ResponsibilitiesDevelop, test, and deploy machine learning and AI models for real-world applicationsBuild and integrate LLM-based features (e.g., chatbots, summarization, RAG pipelines)Work with structured and unstructured data for training and fine-tuning modelsImplement APIs and backend services to serve AI models in productionOptimize model performance, latency, and scalabilityCollaborate with cross-functional teams in an Agile development environmentParticipate in code reviews, experimentation, and model evaluationRequired Skills1–2 years of hands-on experience in AI/ML developmentStrong proficiency in PythonExperience with ML frameworks such as TensorFlow or PyTorchUnderstanding of NLP concepts and LLM integrationsFamiliarity with REST APIs and backend development conceptsExperience working with vector databases or embeddings (preferred exposure)Strong problem-solving skills and analytical thinkingGood communication skillsNice to HaveExperience with Generative AI frameworks (e.g., LangChain or LangGraph)Exposure to cloud platforms like AWS, Azure, or GCPFamiliarity with Docker and basic DevOps conceptsExperience with knowledge graphs or graph databasesUnderstanding of RAG (Retrieval-Augmented Generation) pipelinesEducationBachelor’s or Master’s Degree in Computer Science, Engineering, Data Science, or a related field