• End-to-end development of Seed-X products and features - spec to client. • Integrating with diverse systems ranging from big data pipelines to distributed system to and edge devices built by Seed-X and its vendors. • Own microservices end-to-end. • Collaborate with Designers, Product Managers, and peers to deliver amazing products. • Maintain and develop our Data tagging and Biological Experiments Management tools and systems. • Analyze and improve precision, scale, and stability of Seed-X products, environments, and tools. • Continuously learn and evaluate new technologies in an ongoing effort to discover and evolve better solutions and infrastructure.

Role Description We're looking for a Software Engineer who has already crossed that line. Someone for whom AI tools are a first-class part of daily engineering practice, and who brings the same instinct to designing, leading, and shipping AI-powered systems for our clients. Concretely, you will: - Build LLM-based applications, agentic workflows, and AI-powered features that are production-ready and maintainable. - Implement retrieval pipelines, tool integrations, and orchestration logic within agentic systems. - Contribute to evaluation and monitoring practices for AI systems in production, helping measure and improve output quality over time. - Integrate AI capabilities into existing products and architectures with attention to reliability and performance. - Collaborate with senior engineers and product stakeholders to understand use cases and translate them into working solutions. - Use AI coding tools (Claude Code, Cursor, Copilot, or similar) as a meaningful part of your development workflow, not just occasionally. - Stay current with the AI tooling ecosystem and contribute informed perspectives on what's worth adopting. - Grow your scope progressively, with team support, toward end-to-end ownership of AI system components. Qualifications - 2+ years of experience building production software systems, with exposure to AI or ML-driven features. - Working understanding of modern AI concepts: LLMs, embeddings, retrieval systems, and at least the basics of agentic design patterns. - Solid engineering fundamentals (Python and/or TypeScript/Node.js) and experience contributing to backend services in production. - Ability to implement well-scoped solutions from clear technical direction, and to flag when scope or approach needs discussion. - Thinks about whether an agent or model-driven approach could fit a problem before defaulting to traditional code. - Genuine curiosity about how AI systems work, not just as a user, but as someone who wants to understand and improve them. - Growth mindset: you're honest about what you don't know and proactive about closing the gap. - Comfort with day-to-day ambiguity: you can make progress even when the full picture isn't clear. - Pragmatic instincts: you'd rather ship something good than stall waiting for something perfect. - Clear communicator who asks good questions and knows when to seek input. Requirements - Has used AI coding tools (Cursor, Claude Code, Copilot, etc.) as a meaningful part of a real project and can speak to what that changed. - Has built a small agentic workflow, LLM-powered tool, or AI-assisted automation, even as a side project or exploration. - Familiar with evaluation and testing approaches for AI outputs (prompt testing, output comparison, basic regression). - Has experimented with frameworks or tools in the AI ecosystem: LangChain, LlamaIndex, LangGraph, Anthropic tool use, OpenAI function calling, or similar. - Has replaced something they did manually with an AI-driven workflow and can describe what they learned. - Reads about AI developments with genuine interest and forms opinions about them. Benefits - Access to frontier AI as part of your daily work: latest models and tooling available without an approval gauntlet. - A team that already works this way. You won't be the only one rethinking how engineering gets done. - Agile Company Culture and the Best Team. - Global Projects & Opportunities. - Social Events & Team Building. - Continuous Development: Training & Development, Growth Opportunities. - Flexible Working: Remote Friendly Culture. - Great Equipment & Tools. - Flexible Benefits. - Extra Days Off. - Health Insurance. Hiring Process Our process is direct and designed to respect your time: - PX interview - Technical interview - Final conversation - Offer * The technical interview focuses on real problems, not algorithmic puzzles. We evaluate candidates holistically. If you don't meet every requirement listed above, apply anyway. We care more about how you think and work than whether your CV matches a checklist. See you on the other side!

Role Description - Entwicklung und Implementierung von benutzerfreundlichen Frontend-Komponenten unter Verwendung von Vue.js. - Entwerfen und Entwickeln von skalierbaren Backend-Lösungen mit Python. - Zusammenarbeit mit UX-Designern zur Optimierung der Benutzererfahrung und Verbesserung der Nutzeroberflächen. - Pflege und Optimierung bestehender Applikationen zur Steigerung der Leistung und Effizienz. - Durchführung von Code-Reviews und Sicherstellung von qualitativ hochwertigem Code durch Best Practices. Qualifications - Abgeschlossenes Studium der Informatik oder eine vergleichbare Qualifikation. - Mehrjährige Berufserfahrung in der Entwicklung von Webanwendungen mit Python und Vue.js. - Erfahrung in der Gestaltung von benutzerfreundlichen UX/UI-Designs. - Fundierte Kenntnisse in modernen Web-Technologien und Frameworks. - Selbstständige Arbeitsweise und Fähigkeit, remote im Team zu arbeiten. Requirements - Erfahrung mit FastAPI, Playwright und pytest. - Datenbankkenntnisse: PostgreSQL. - LDAP-Know-how.

Role Description We're looking for a Senior Software Engineer who has already crossed that line. Someone for whom AI tools are a first-class part of daily engineering practice, and who brings the same instinct to designing, leading, and shipping AI-powered systems for our clients. Concretely, you will: - Lead the design and implementation of multi-step agentic pipelines, LLM-based applications, and AI-powered workflows, taking end-to-end responsibility from architecture through to production. - Define and own evaluation frameworks and feedback loops for AI systems in production: prompt regression suites, output quality monitoring, and continuous improvement cycles. - Make architectural decisions on AI system design (model selection, orchestration strategy, retrieval approach, latency and cost trade-offs) and explain the reasoning clearly to engineering and product stakeholders. - Identify high-impact AI opportunities in complex client environments, translate them into actionable technical proposals, and lead their execution. - Integrate modern AI capabilities (agentic orchestration, structured generation, tool use, model routing) into existing architectures with a clear eye on reliability and maintainability. - Set the bar for engineering practice on the team: code quality, observability, evaluation rigour, and responsible AI deployment. - Use AI coding tools (Claude Code, Cursor, Copilot, or similar) as a primary part of your development workflow, not an occasional aid, and help the team level up in how they work. - Stay at the frontier of the AI tooling ecosystem and bring informed opinions on what's worth adopting into practice. Qualifications - 5+ years of experience building production software systems, with at least 2 years working on AI or ML-driven features in production. - Deep understanding of modern AI concepts: LLMs, embeddings, retrieval systems, agentic design patterns, evaluation frameworks, and observability for AI systems. - Strong engineering fundamentals (Python and/or TypeScript/Node.js) and a track record of building reliable, scalable backend services. - Demonstrated ability to lead technical decisions (architecture, trade-offs, technology selection) and communicate them clearly across engineering and product. - Experience designing and owning systems under real-world constraints: performance, cost, reliability, and long-term maintainability. - Ability to take ambiguous, open-ended problems and drive them to well-scoped, shippable solutions with minimal direction. - High agency: you operate autonomously, make decisions, and flag clearly when you need input. - Defaults to asking "can an agent or model handle this?" before reaching for a traditional approach, and knows when the answer is no. - Pragmatic over perfectionist: you know when "good enough in production" beats "perfect in theory," and when it doesn't. - Low ego, high standards: you hold the bar without holding the room hostage. Requirements - Has shipped real products using AI-assisted coding workflows and can speak concretely to what changed in their engineering process. - Has designed and operated LLM evaluation harnesses, red-teaming pipelines, or output regression frameworks at scale. - Active user of (or contributor to) the emerging AI tooling ecosystem: MCP, agent protocols, model routers, LLMOps tooling. - Experience with the full prompt engineering lifecycle in production: versioning, A/B testing outputs, and monitoring for drift. - Has rebuilt an internal workflow or tool they previously did manually by replacing it with an agentic system, and can describe what they learned. - Comfortable reading frontier AI research and forming opinions on what's worth adopting versus what's hype. - Experience mentoring or technically guiding other engineers on AI system design. Benefits - Access to frontier AI as part of your daily work: latest models and tooling available without an approval gauntlet. - A team that already works this way. You won't be the only one rethinking how engineering gets done. - Agile Company Culture and the Best Team. - Global Projects & Opportunities. - Social Events & Team Building. - Continuous Development: Training & Development, Growth Opportunities. - Flexible Working: Remote Friendly Culture. - Great Equipment & Tools. - Flexible Benefits. - Extra Days Off. - Health Insurance. Hiring Process Our process is direct and designed to respect your time: - PX interview - Technical interview - Final conversation - Offer * The technical interview focuses on real problems, not algorithmic puzzles. We evaluate candidates holistically. If you don't meet every requirement listed above, apply anyway. We care more about how you think and work than whether your CV matches a checklist. See you on the other side!