AI Product Builder
AI Product Builders at n8n own one focused AI workstream where they are close to users, technology, and the future of AI products. They work either independently or alongside a senior PM as a mentor and collaborate closely with cross-functional teams including Engineering, Design, Data, Product Marketing, DevRel, Community, Support, and Customer Success. The role is not focused on ML platform or research but involves building with AI deeply through products, prototypes, public projects, agent workflows, or tools used by real users. Possible workstreams include AI TRUST, which focuses on improving AI quality, observability, reliability, and human-in-the-loop patterns to make AI work in production, and AI BUILDING / SUPER AGENT, which focuses on making n8n an AI-first product by shifting usage to AI-native interfaces and features such as Super Agent, custom memory, Skills, and proactive suggestions.
AI Deployment Engineer - Startups
Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value. Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into clear, reproducible evaluations, benchmarks, and technical artifacts that improve model and product quality and ensure customer-grounded learnings influence roadmap and model development. Build repeatable tools, patterns, and evaluation approaches that raise the quality bar across multiple use cases. Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement. Build relationships within the startup ecosystem, serving as a technical partner to both individual customers and the broader community.
Software Engineer (Brazil)
Design, develop, test, deploy, maintain, and improve scalable, secure, and high-performance backend systems with a focus on high availability, low latency, and cost-effectiveness. Act as the subject matter expert in infrastructure when designing new products and introducing new technology to existing products. Collaborate closely with engineering and research teams to integrate infrastructure components with product features to optimize system performance and user experience. Design event-driven architectures and develop APIs and microservices for real-time processing and analytics. Ensure system reliability, performance, and scalability through monitoring, logging, and error handling. Stay current with emerging trends, technologies, and methodologies to enhance infrastructure capabilities. Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
Freelance n8n Workflow Developer - AI Trainer
As an n8n Workflow Developer on the Tendem project, the responsibilities include designing, building, and evaluating advanced workflows in self-hosted n8n environments, architecting multi-system integrations for scalable automation pipelines, developing and optimizing AI-powered workflows such as content generation and enrichment systems, building and maintaining lead generation, outreach, and data processing automation systems, implementing web scraping workflows, and ensuring reliable data extraction and processing. Additionally, the role involves optimizing workflow execution, node sequencing, and error handling to prevent failures, delays, and API timeouts, as well as collaborating with Tendem Agents to provide structured thinking, automation expertise, and quality control for efficient and reliable workflow execution.
Scientific Software Engineer (Polymer Simulations)
Design and implement atomistic simulation workflows for polymer systems, including polymerisation and melt equilibration through to production runs. Implement complementary simulation techniques beyond molecular dynamics (MD) to address complex industry problems. Collaborate with AI research teams to integrate machine learning models into atomistic simulation workflows. Work closely with experimental partners to validate and ensure simulation outputs align with real lab measurements and trends are reproducible and explainable. Translate materials challenges from partners into simulation strategies and deliver clear, rigorous findings suited for industrial collaborations. Serve as an internal expert on polymer science to guide AI researchers on physical constraints and material behaviours. Collaborate across teams of machine learning researchers, computational chemists, and experimentalists contributing independently and leveraging complementary expertise. Contribute to the development of CuspAI's core infrastructure and roadmap for multi-scale materials discovery.
AI/ML Engineer
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices, incorporating them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
AI Product Manager
As an AI Product Manager, you will define and drive the AI product roadmap ensuring alignment with business objectives and user needs. You will collaborate with cross-functional teams including engineering, design, and marketing to develop and launch AI-powered features. Responsibilities include conducting market research and analyzing user feedback to identify opportunities for AI integration, working closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact, defining key performance indicators to measure success and iterating based on data-driven insights, staying up to date with AI trends, emerging technologies, and best practices, and ensuring ethical AI usage and compliance with data privacy regulations. This role is fully onsite in Lisbon, involving close in-person collaboration in a dynamic and fast-paced environment.
Manager, Forward Deployed Engineering - Munich
Lead and grow a team of Forward Deployed Engineers (FDE) delivering production systems with frontier models. Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality. Codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and the wider developer community. Identify and raise early indicators with urgency from product behavior, customer environments, or delivery practices. Use judgment to decide when action is required. Set high performance standards for FDEs and support each individual's growth through direct, actionable feedback. Define staffing and support strategies for scalable field teams without added complexity.
AI Product Manager, Berlin
Define and drive the AI product roadmap, ensuring alignment with business objectives and user needs. Collaborate with cross-functional teams, including engineering, design, and marketing, to develop and launch AI-powered features. Conduct market research and analyze user feedback to identify opportunities for AI integration. Work closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact. Define key performance indicators (KPIs) to measure success and iterate based on data-driven insights. Stay up to date with AI trends, emerging technologies, and best practices to ensure products remain competitive. Ensure ethical AI usage and compliance with data privacy regulations.
AI/ML Engineer, Berlin
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into the applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices, incorporating them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
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