AI Engineer

📋 Description

• • Design, develop, and ship AI-driven capabilities including agents, intelligent assistants, context-aware predictions, and generative AI using Python, LLMs (OpenAI, Anthropic Claude, Google Gemini), TypeScript, React, Canvas, and WebGL.
• • Engineer high-performing AI workflows leveraging prompt engineering, generative techniques, and top-tier LLMs, ensuring reliability, scalability, and maintainability in production.
• • Execute end-to-end AI projects from conceptualization and prototyping to production deployment, collaborating closely with product managers, designers, and engineers.
• • Experiment and iterate on AI capabilities within your team domain, staying ahead of emerging AI tools, frameworks, and techniques to drive innovation.
• • Champion best practices in AI system development including evaluation frameworks, LLMOps, CI/CD, observability, and ethical AI principles.
• • Measure and optimize AI performance by establishing benchmarks for user engagement, model accuracy, latency, error rate, and drift.
• • Write clean, well-tested, and maintainable code while actively participating in code reviews and technical discussions across engineering teams.
• • Troubleshoot and resolve production issues to ensure high availability, performance, and stability of AI-powered features on Miro’s collaborative canvas.
• • Translate complex technical concepts into clear communication for non-technical stakeholders to align product vision with engineering execution.
• • Build production-ready AI systems within complex codebases, integrating AI capabilities into Miro’s real-time, visual workspace platform.
• • Apply ML fundamentals including probabilistic modeling, evaluation techniques, and deep neural networks to improve model selection and feature quality.
• • Utilize cloud services such as AWS, Azure, or Amazon Bedrock to deploy and manage AI infrastructure at scale.
• • Demonstrate AI-First Proficiency by integrating AI agents into daily development workflows—for example, using AI for autonomous debugging, log analysis, or rapid prototyping to ship high-quality code at an ambitious pace.
• • Explore and implement advanced AI techniques such as RAG pipelines, vector databases, LangChain, or agent frameworks to enhance user experiences.
• • Leverage multi-modal AI or long-context handling capabilities where applicable to expand the scope of intelligent features on the canvas.
• • Apply rendering technologies like WebGL, Canvas API, or 2D graphics libraries (PixiJS, Skia) to enhance visual AI interactions within the Miro platform.
• • Work with real-time technologies such as WebSocket to enable responsive, low-latency AI interactions in collaborative environments.