AI Product Engineer

Job Title: AI Product Engineer Responsibilities AI product strategy planning: Conduct in-depth research on industry trends, user needs, and technical feasibility, and formulate a medium‑to‑long‑term roadmap for AI products based on the company's business objectives, clarifying product positioning, core functions, and implementation paths. AI Technology Collaboration: Work closely with algorithm engineers and R&D engineers to evaluate technical implementation challenges, determine model selection (e.g., fine‑tuning large models, Prompt Engineering, multimodal fusion), data requirements, and engineering implementation architecture. Product Prototyping and Interaction Design: Lead AI product prototyping (using Axure/Figma) to optimize intelligent interaction logic (including dialogue flow, command comprehension, and feedback mechanisms), ensuring a balance between usability and intelligent experience. Full‑cycle project management: As the AI product lead, coordinate project timelines and resource allocation, oversee the entire development process from R&D to testing and launch, resolve cross‑departmental collaboration challenges, and ensure timely and high‑quality product delivery. Data‑driven iteration: Build an AI product evaluation system to monitor core metrics (such as accuracy, recall rate, user retention, and interaction efficiency), and continuously optimize product features and algorithm performance through user feedback and data review. Cross‑domain knowledge accumulation: Build AI product design methodologies and best practices for technical implementation, deliver product documentation and technical handbooks to enhance team capabilities in AI product development. Industry Ecosystem Integration: Stay updated on cutting‑edge AI technologies (e.g., GPT‑4, Wenxin Yiyan, multimodal models) and competitor trends, exploring innovative integration scenarios between technology and business operations. Qualifications Education and Major: Bachelor's degree or above, with preference for majors such as Computer Science, Artificial Intelligence, Data Science, or Software Engineering. At least 3 years of experience in AI products or smart products. Core Competencies: Possess solid AI foundational knowledge (including machine learning, principles of large models, and NLP/computer vision fundamentals), and be proficient in at least one AI implementation process (such as fine‑tuning large models, API calls, data annotation, and training). Product Mindset: Candidates should demonstrate sharp demand insight and logical analytical skills to define AI product value from a business perspective, balancing technical feasibility with user experience. Preference will be given to those with full experience in developing AI products from concept to implementation. Collaboration and Communication: Excellent cross‑departmental collaboration skills, able to effectively connect with algorithm, R&D, design, marketing and other teams, clearly convey product requirements and technical logic, and promote the implementation of complex projects. Learning and Innovation: Highly sensitive to cutting‑edge AI technologies and product trends, with strong learning agility to adapt to rapid technological iterations. Candidates with innovative product designs or proven technical implementation experience will be prioritized. Bonus points: Experience in large model products, enterprise‑level AI services, or smart hardware; Familiarity with mainstream AI development platforms (e.g., OpenAI, Alibaba Cloud PAI, Baidu Intelligent Cloud) or AI tools (e.g., LangChain, MidJourney); Ability to read technical documentation and understand basic algorithmic principles. Benefits Competitive salary and benefits. A challenging and growing work environment. #J-18808-Ljbffr