AI Engineer

Position Summary We are seeking a mid-level AI Engineer to join our team focused on building scalable, production-ready AI solutions that support analytics, automation, and intelligent decision-making. This role will contribute to the development and deployment of machine learning models, generative AI systems, and AI-enhanced data workflows across platforms. Key Responsibilities Model Development Deployment : Design, train, and deploy machine learning and deep learning models using frameworks like TensorFlow, PyTorch, and Scikit-learn. Generative AI LLMs : Implement and fine-tune large language models (LLMs) using tools such as LangChain, RAG, and vector databases. Experience with GPTs, LLaMA, or similar models is preferred MLOps GenAIOps : Use tools like MLflow and Docker to manage model lifecycle, reproducibility, and scalability. Support production-grade GenAI systems Data Engineering Collaboration : Work closely with data engineers to ensure robust data pipelines and infrastructure for model training and inference. Integration APIs : Develop APIs and microservices to integrate AI models into enterprise applications and workflows. Monitoring Optimization : Continuously monitor model performance and retrain as needed to maintain accuracy and relevance. Security Governance : Ensure AI systems comply with enterprise security and data governance standards. Skills Qualifications 35 years of experience in AI/ML engineering or related roles. Proficiency in Python and experience with AI frameworks (TensorFlow, PyTorch). Familiarity with cloud platforms (AWS, Azure, GCP) for model deployment. Experience with MLOps tools (MLflow, Docker) and GenAI deployment. Strong understanding of LLMs, NLP, and computer vision techniques. Ability to write clean, efficient, and reusable code. Experience with RESTful APIs and microservices architecture. Preferred Experience Exposure to educational technology or enterprise data environments. Experience integrating AI into transactional systems. Familiarity with data warehouses and data governance frameworks.