AI Technical Leader

We are seeking a strategic and hands-on AI Technical Leader / Agent Architecture Lead to build and scale our medical AI intelligent agent ecosystem. This role owns end-to-end technical strategy, architecture design, core R&D, team management, and compliance governance for medical AI scenarios including medical Q&A, imaging analysis, and auxiliary diagnosis. Ideal for a technical entrepreneur with solid engineering capabilities, long-term tech vision, and genuine passion for healthcare AI, you will lead 0-to-1 innovation and drive business value delivery in a fast-growing startup environment.

About the Role

Key Responsibilities

Technical Strategy & Architecture Design

• Formulate mid-to-long-term technical roadmaps, and lead the end-to-end agent architecture design for healthcare scenarios such as medical question answering, medical imaging analysis, and clinical auxiliary diagnosis.
• Balance technical forward-thinking and business alignment.
• You will also participate in hands-on core development: implement critical Agent workflows, optimize RAG performance, troubleshoot and resolve complex technical bugs, and develop high-quality code standards and demos for the team.

Core R&D & Infrastructure Construction

• Lead the research and development of medical-specific large model foundations, customized Agent frameworks (RAG, tool calling, etc.), medical knowledge graphs, and unified data processing platforms.
• Build highly available, scalable enterprise-level Agent infrastructure to underpin all medical AI product lines.

Team Building & Technical Management

• Build and lead a cross-functional technical team of 10–15 members, covering algorithm research, algorithm engineering, service architecture, and backend development.
• Establish streamlined R&D workflows and cultivate a high-performance, excellence-driven engineering culture.

Medical Compliance & AI Security Governance

• Develop end-to-end risk control systems compliant with healthcare data security standards (HIPAA), data privacy regulations, and AI content governance requirements.
• Ensure full compliance as the fundamental prerequisite for clinical deployment and patient-oriented medical AI services.

Cross-Functional Collaboration & Business Empowerment

• Partner closely with product, clinical, marketing and other cross-functional teams to seamlessly integrate agent capabilities into product portfolios.
• Leverage cutting-edge AI technology to fuel business growth and deliver tangible value to customers and medical institutions.

Technical Evaluation & Quality Assurance

• Establish comprehensive evaluation frameworks for agent performance, response accuracy, and system reliability.
• Meet the strict stability, credibility and safety requirements of clinical and medical application scenarios.

Qualifications

Required Qualifications

• Master’s degree or above in Computer Science, Software Engineering, Artificial Intelligence, Biomedical Engineering, or related technical fields; top-tier university background is highly preferred.
• 8+ years of hands-on technical experience in the internet/AI industry, with 3+ years of formal technical team management experience.
• Proven 0-to-1 experience in building complex AI systems or intelligent agents, with at least one fully launched and commercially validated AI project.
• Proficient in Python, mainstream deep learning frameworks (PyTorch/TensorFlow), and cloud-native tech stacks (Docker, Kubernetes).
• In-depth understanding and practical application experience with RAG, prompt engineering, function calling, mainstream Agent frameworks (LangChain, CrewAI), and LLM fine-tuning (SFT/RLHF).
• Strong capabilities in unstructured and semi-structured data processing, with full-cycle engineering experience in data collection, cleaning, vectorization and knowledge base construction.

Soft Skills & Industry Mindset

• Outstanding team building, talent development and cross-departmental collaboration skills; influential in technical decision-making and capable of unlocking team potential.
• Proactive technical initiative and strong entrepreneurial mindset; comfortable with high uncertainty and fast-paced 0-to-1 innovation.
• Deep industry insight and genuine passion for healthcare; familiar with medical AI commercialization paths, compliance challenges, and real pain points of physicians, patients and medical institutions.
• Business-oriented thinking to translate cutting-edge AI technologies into scalable commercial value, rather than pursuing technology for technology’s sake.

Preferred Skills

• Proven track record of launching medical AI or multimodal large model products, with solid experience in medical data processing and industry specifications.
• First/co-first author publications in top AI conferences including NeurIPS, ICML, ACL, CVPR.
• Startup background or end-to-end 0-to-1 product building experience; adaptable to fast-paced, resource-constrained startup environments.
• Practical experience in hardware acceleration, high-performance computing, or large-scale distributed system optimization.