Jobs at Patsnap

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.

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

Manage and grow a portfolio of enterprise accounts in ASEAN through full sales cycles, renewal and expansion, upsell/cross-sell, stakeholder engagement with R&D/IP/legal teams, onboarding, QBRs, and issue resolution to hit growth and retention targets.

Support growth marketing by monitoring PLG metrics, designing A/B tests, collaborating with Product and Engineering, using AI tools and automation, conducting market research, and executing cross-channel campaigns to drive user acquisition and engagement.

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.

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.

Support design of an AI-powered formulation agent by translating complex workflows into user journeys, wireframes, and prototypes. Assist with research, information architecture, dashboards, interaction flows, visual assets, usability testing, and design iteration while collaborating with the product team.

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.