ButterflyMX

AI Solutions Engineer

ButterflyMX

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSAzureCloudGoogle Cloud Platform

About the role

  • Rapidly prototype, test, and deploy AI-powered tools such as copilots, automations, knowledge assistants, and agents
  • Implement RAG pipelines, prompt engineering, and orchestration frameworks (LangChain, LlamaIndex, etc.)
  • Partner with business teams to understand workflows and identify opportunities for AI acceleration
  • Work closely with data, engineering, and security teams to ensure reliability, scalability, and compliance of deployed solutions
  • Maintain and contribute to a backlog of AI initiatives, prioritizing those with clear business impact
  • Monitor performance and adoption, track KPIs, and iterate on solutions to maximize effectiveness
  • Contribute to internal documentation, demos, and training to help colleagues become fluent AI users
  • Provide technical support during workshops, office hours, and stakeholder pilots
  • Evaluate emerging AI platforms, frameworks, and APIs with a pragmatic lens for business value
  • Share insights with the team and contribute to scaling best practices into playbooks and repeatable patterns

Requirements

  • Strong hands-on experience as a technical IC (e.g., software engineering, ML, data engineering, or automation)
  • Proficiency with modern AI tooling (OpenAI, Claude, LangChain, Hugging Face, vector DBs, agents, RAG pipelines)
  • Demonstrated ability to scope, build, and deliver working solutions from idea to impact
  • Solid understanding of APIs, data pipelines, and software deployment practices
  • Excellent problem-solving and communication skills. You can explain technical concepts clearly and engage with non-technical stakeholders
  • Experience with cloud platforms (AWS, GCP, Azure) and containerized deployments (preferred). Previous work on copilots, chatbots, or workflow automation tools (preferred)
  • Strong product sense, you can see through the hype to spot practical, high-leverage use cases (preferred)
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