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AI Technical Architect
Miro · New York, United States
About The Role
Join Miro as an AI Technical Architect, where you'll support strategic customers in designing and deploying AI solutions that enhance collaboration and drive business outcomes. You'll serve as a trusted advisor and technical lead on various AI use cases, guiding customers through onboarding and implementation. This role requires hands-on experience integrating AI into enterprise SaaS environments, excellent communication skills, and a strategic mindset.
- Lead customer discovery sessions to identify AI use cases, data sources, technical constraints, and automation opportunities.
- Design and implement AI-driven solutions in Miro, including intelligent templates, agents, summarization tools, and custom GPT integrations.
- Serve as a trusted advisor on AI solution architecture, including data privacy, compliance, API usage, and model performance monitoring.
- Hands-on experience integrating AI into enterprise SaaS environments using APIs or low-code tools
- 6+ years of experience in a technical consulting, solution architecture, or professional services role with customer-facing responsibilities
- Excellent facilitation and communication skills with the ability to explain complex AI concepts to a non-technical audience
- Knowledge of enterprise AI safety, data privacy, and responsible deployment practices
- Knowledge of REST APIs and experience with low-code/no-code automation platforms is a strong plus
- Strategic mindset with a bias toward experimentation, iteration, and learning
- Experience designing, evaluating, and deploying AI agents or workflows using frameworks like LangChain, CrewAI, or AutoGPT
- Strong familiarity with AI tooling and APIs (e.g. OpenAI, Hugging Face, Vertex AI), and knowledge of how to integrate these within customer workflows
- Curiosity and empathy—especially when it comes to understanding a customer’s needs and how AI can uniquely solve them
- Hands-on experience designing or implementing AI solutions, including working with LLMs, prompt engineering, and/or agent frameworks (e.g. AutoGPT, LangChain, RAG)
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