Artificial Intelligence Engineer, Miro

• A solid grounding in machine learning fundamentals, including probabilistic modeling and deep neural networks
• Demonstrated track record in prompt engineering and context engineering using top-tier LLMs—e.g., OpenAI GPT models, Anthropic Claude, Google Gemini
• Experience delivering AI-first capabilities in customer-facing products—driving value through features users directly interact with
• Comfortable translating and communication complex technical concepts fo r non-technical stakeholders in user-facing documentation or demos
• Option A: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related STEM field plus ~3 years of professional AI/ML experience
• Option B: No formal degree, ~6 years of self-taught or industry experience demonstrating equivalent proficiency

Desirable

• Our team’s mission is to drive AI-powered success and innovation in Miro by building robust technical foundations and delightful, intelligent product features
• We empower both internal and external teams to innovate with AI efficiently and responsibly
• We believe the future of Miro is AI-augmented — and we’re building the path to get there
• As an AI Engineer at Miro, you will play a key role in designing, developing, and shipping the AI-driven capabilities that enhance Miro's customer experience from ideation to delivery
• You will be responsible for engineering high-performing AI workflows that power features like intelligent assistants, context-aware prediction, and generative AI
• Design, develop, and ship AI-driven capabilities—including agents, intelligent assistants, context-aware prediction, and generative AI—that enhance Miro’s customer experience, from ideation to delivery
• Execute end-to-end ML projects: from conceptualizing use cases to prototyping, training, evaluating, and deploying models into production
• Engineer high-performing AI workflows leveraging off-the-shelf large language models (OpenAI, Anthropic Claude, Google Gemini, etc.), prompt engineering, retrieval-augmented generation (RAG), and generative techniques—ensuring reliability, scalability, and maintainability
• Collaborate cross-functionally with product managers, designers, engineers, and researchers to translate business goals into AI solutions, and to iterate rapidly through feedback and experimentation
• Champion best practices in AI system development—including evaluations, reproducibility, MLOps, CI/CD, observability, and version control—aligned with ethical AI and responsible development principles
• Measure and optimize AI performance, establishing benchmarks for outcomes like user engagement, model accuracy, latency, error rate, and drift
• Stay ahead of the curve by evaluating emerging AI tools, frameworks, and techniques—and advocating for their application across Miro