About the role
Our Why At Dotmatics At Dotmatics, we believe science, data, and decision-making must be deeply intertwined for innovation to thrive. Our Portfolio includes Luma, LumaLab Connect, ELN Platform, Graphpad Prism, Geneious, SnapGene, Protein Metrics, OMIQ, FCS Express, LabArchives, NQuery, EasyPanel, MStar, SoftGenetics and Virscidian. We have a vision for a new Lab of the Future that will change the future of scientific research. We have created the world’s most comprehensive digital science platform – best-of-breed software applications already used by more than 2 million scientists, together in a single ecosystem united by a powerful, flexible enterprise data platform. This is not flat data buried away in digital graveyards. This is dynamic, multi-dimensional decision-making. Scientific enterprises need a new level of effectiveness to achieve tomorrow’s breakthroughs. Illness will not wait. The biosphere will not wait. We are tireless in our vision, because the time for innovation is now. Shaping the Future of Science At Dotmatics Our global team of more than 800 colleagues are dedicated to supporting our customers in over 180 countries. Together, with our scientific community of users, we accelerate scientific innovation in order to make the world a healthier, cleaner, and safer place to live. You’ll join a collaborative, global team pushing the boundaries of scientific innovation. Your ideas and efforts will have a tangible impact, accelerating scientific progress and discovery. We offer a dynamic, remote-friendly environment that fosters high integrity and collaboration, empowering you to excel. Dotmatics is a company built by scientists, for scientists. Combined, we are now the world’s largest cloud-based scientific research R&D platform. We need your help to keep growing and pioneering the future. We are Science Driven. We are Customer Centric. We are Better Together. What do we need We are seeking a Senior AI Engineer (Full stack) with advanced Python skills to join our team building and advancing the Luma platform—an AI-Native Multimodal Research Platform for Scientific Intelligence. A platform that helps customers analyze and configure data within their system. This role offers the opportunity to work on cutting-edge AI/ML technology, architecting scalable microservices, and delivering production-ready systems that integrate with enterprise data platforms. You will build AI agents that perform real work—systems that plan tasks, call tools, execute workflows, interact with APIs, and integrate with real-world data sources. You'll be working in a collaborative, agentic coding environment where modern development tools support your workflow, enabling rapid iteration while maintaining high code quality standards. In this role you will get to Development & Implementation Design and implement AI agent workflows and tooling using LangChain/LangGraph, enabling AI models to plan actions, call tools, use APIs, search information, and reliably complete multi-step workflows. Build and maintain the tools, function interfaces, and system connectors that AI agents use to interact with databases, document stores, enterprise apps, and external APIs. Ensure AI agents operate safely, follow rules, respect permissions, and reliably execute within defined constraints. Lead and execute the design and implementation of core workflow orchestration and tooling features, including automated tasks and background processes. Build scalable FastAPI services with well-defined RESTful APIs and real-time streaming endpoints. Create modular, reusable service components with strong authentication, error handling, and pagination patterns. Develop and guide React frontend components for real-time interactions and data visualization. Implement multi-tenant architecture with secure isolation, resource boundaries, and long-term scalability. Provide technical guidance to other engineers during implementation, ensuring high-quality, maintainable solutions. Evaluate risk when implementing new features or refactoring, and propose safe rollout strategies. Architecture & Design Clean Architecture principles with clear separation of concerns Microservices design patterns including service discovery, API gateways, and interservice communication Event-driven architecture with message queues and async processing Subprocess isolation patterns for credential management and security boundaries Influence architectural direction across teams, helping bring clarity and structure to ambiguous problems. Architect robust AI agent execution layers that ensure determinism, observability, and reliable stepwise execution. Quality & Operations Write comprehensive automated tests using pytest and Jest, including integration and behaviour-driven tests. Implement structured logging, correlation IDs, and observability patterns to ensure system clarity and operability. Contribute to and improve CI/CD pipelines with automated testing, linting, and deployment workflows. Set up effective monitoring and alerting for production systems. Lead or support critical incident resolution with calm, context-driven decision-making. Drive platform-wide improvements in performance, reliability, and technical quality. Exercise independent judgment in methods, techniques, and evaluation criteria to ensure robust outcomes. Instrument AI agent systems with monitoring, tracing, and guardrails to ensure safe and predictable behaviour in production. Collaboration & Documentation Document architectural decisions, engineering patterns, and approaches that become long-term references for