Ai Full Stack Developer

Job Title: Middle AI Full Stack Developer San Jose, CA Work Hours: 8:00~17:00 CST Job Summary We are looking for a highly motivated AI Full Stack Developer to join our team to build, deploy, and maintain end-to-end applications that leverage generative AI models and agentic architectures. As a Full-stack AI Developer, will bridge the gap between AI research and production-ready applications, working across the entire stack from frontend interfaces to backend logic and machine learning models. Will be responsible for building, testing, and scaling AI-driven products. Key Responsibilities AI Application Development: Develop and maintain end-to-end AI applications, from user interfaces to backend logic, focusing on AI-powered features. ML Model Integration: Implement machine learning models (using frameworks like PyTorch, TensorFlow, or scikit-learn) into web and mobile applications. Backend & API Engineering: Build and maintain scalable backend services and RESTful APIs, often integrated with large language models (LLMs) and agentic frameworks. Frontend Development: Create interactive, responsive front-end components for user interfaces using modern frameworks like React, Vue, or Next.js. MLOps & Deployment: Manage end-to-end life cycles for production, including deployment workflows using Kubernetes, Cloud Run, or containerization tools to ensure high-performance applications. Database Management: Manage both relational and NoSQL databases to support AI-powered functionality. Collaboration: Work closely with data scientists, product managers, and designers to turn AI capabilities into user-focused products. Required Qualifications & Skills Experience: Proven experience (5~8 yrs. for Middle Level) as a Full Stack Developer with specialized experience in AI model deployment. Backend Skills: Strong proficiency in Python and frameworks like FastAPI or Django. AI/ML Knowledge: Familiarity with AI model integration (e.g., OpenAI API, LangChain, PyTorch). Cloud/DevOps: Experience in Cloud platforms (AWS, GCP, Azure) and container technologies (Docker, Kubernetes). Education: Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. Preferred Qualifications Experience with generative AI and agentic architectures. Understanding of data privacy and security in AI applications. PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. #J-18808-Ljbffr