Jobs at Patsnap

Work with enterprise customers to design and deploy AI-native solutions: configure AI Agent workflows, build prototypes, support POCs, translate needs into reusable product capabilities, and ensure delivery quality and compliance.

Conduct and analyze patent searches (novelty, invalidity, FTO, state-of-the-art), prepare reports, migrate patent data and Boolean queries across databases, ensure quality of search strategies, manage professional services delivery, work with AI-enabled patent tools, and validate AI outputs to support R&D, innovation, legal, and IP teams.

The role involves architecting and implementing robust Java backend solutions, optimizing performance, leading projects, and collaborating with multiple teams while ensuring code quality.

Seeking a Semiconductor Reverse Engineering Specialist to develop AI-driven solutions, collaborating on workflows and knowledge systems while ensuring technical accuracy and validation of AI outputs.

Develop and iterate full-stack AI products for the life sciences domain, optimize data processing and business logic for pharmaceutical accuracy, and rapidly adopt and integrate frontier LLMs, APIs, and AI tools.

Design, implement, and operate patent and related data pipelines: integrate, parse, store, backup, monitor and optimize data quality and processing performance. Collaborate with data architects to improve scalability, stability, and documentation while ensuring data security and regulatory compliance.

Domain scientist who blends deep life sciences expertise with product building to design AI-native tools (MCPs, Skills, Agents). Identify high-leverage use cases across clinical, BD, competitive intelligence, and regulatory workflows; launch rapid research previews, iterate with users, and guide PM and marketing to deliver useful end-to-end products.

Lead and develop an engineering team, improve delivery and system reliability, influence architecture and technical decisions, drive cross-functional projects, and build engineering capability through hiring, coaching, and process improvements.

Design and build company-wide AI knowledge infrastructure and context layers, develop scalable LLM application architecture (RAG, vector DBs, prompt workflows), own end-to-end delivery of internal AI tools, optimize performance and inference, evaluate/integrate AI tooling, and mentor junior engineers while translating business needs into technical roadmaps.

Analyze and manage small-molecule pharmaceutical data, translate R&D needs into data products, build data quality systems, coordinate cross-functional data projects, and apply LLMs and prompt engineering to extract and normalize knowledge from patents and literature.

Build and maintain frontend architecture and interactive UIs for an AI materials product, integrate LLMs and retrieval APIs, implement streaming AI chat and long-content rendering, create data visualizations and dashboards, develop lightweight backend services (Node.js/FastAPI), and manage CI/CD, deployment, and cross-regional collaboration to deliver end-to-end AI application features.

Own design, build, and productionization of LLM-powered agentic systems for materials R&D: tool orchestration, memory and MCP integration, multi-agent skills, evaluation frameworks, and production reliability/observability. Advise product and platform teams and measure system quality with domain experts.

Manage and grow strategic enterprise accounts across Singapore and Southeast Asia. Build senior stakeholder relationships in R&D, IP, legal, and innovation. Drive upsell and cross-sell, lead full account sales cycles, forecast revenue, ensure retention, and collaborate with Customer Success, Product, and Solution Consulting to deliver value and feedback.

The Full Stack Intern will develop web applications and integrate AI features, assist in testing and deployment, and collaborate on business requirements.