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Ai2iO

Forward Deployed Engineer - MEP Design

AI Application EngineeringPosted on Nov 9
Full-timeRemote in USA$99.8k - $123.4k /yr

About the Job

Requirements

  • Strong working knowledge of MEP consulting engineering, including design phases, construction document production, specifications, calculations, coordination, and QA/QC processes.
  • Understand the professional responsibility carried by the Engineer of Record and how it shapes the ways AI can and cannot be used in engineering deliverables.
  • Have hands-on experience building AI-enabled tools or workflows using LLM platforms such as Claude, Microsoft 365 Copilot, or similar, including prompt and workflow design, agents, and evaluating output quality.
  • Have experience evaluating, selecting, and configuring commercially available software and AI tools, with sound judgment about when to adopt an off-the-shelf solution and when to escalate for custom development.
  • Have scripting proficiency in Python or a comparable language, with the ability to automate tasks, work with APIs, and process project data.
  • Have working knowledge of Revit and Bluebeam Revu.
  • Be able to take a defined priority from idea to working tool quickly and iterate based on real use.
  • Be able to communicate clearly with engineers, designers, and IT professionals and translate between design and technical perspectives.
  • Be comfortable working independently within a dual-reporting structure, balancing Design department priorities with AI2IO standards.
  • Demonstrate the ability to leverage AI tools to enhance personal productivity and quality of work output.
  • Demonstrate a commitment to continuous learning and a track record of staying current on AI advancements, AEC industry tools, and emerging best practices.
  • Have a minimum of 5 years of experience in MEP consulting engineering or design, including at least 2 years of hands-on experience building automation, scripting, or AI-enabled tools, whether in a formal role or self-driven.

Responsibilities

  • Translate Design department roadmap priorities into working AI solutions—agents, automations, scripts, prompt libraries, and Claude and Microsoft 365 Copilot workflows—and iterate from requirements to usable tools.
  • Evaluate commercially available AI tools, industry software, and native platform features first; configure off-the-shelf solutions where suitable and pursue custom development only when necessary.
  • Build tools that fit MEP teams’ existing workflows and integrate with design, documentation, and project delivery tools such as Revit, AutoCAD, Bluebeam Revu, Excel-based calculation tools, SharePoint, and Teams.
  • Develop scripts and automations using Python, Dynamo, the Revit API, Power Automate, approved AI platforms, and other approved tools where off-the-shelf features are insufficient; keep custom code lightweight and maintainable.
  • Build knowledge and retrieval solutions that let engineers search and reuse department standards, design guides, specifications, and past project documentation.
  • Deploy, maintain, troubleshoot, and improve department-level tools within AI2IO security, data-handling, and governance standards as platforms, models, and department needs evolve.
  • Hand off solutions requiring custom or enterprise-scale development to AI2IO’s DevOps team through the Software Development Lifecycle (SDLC), with sufficient documentation and requirements for an effective handoff.
  • Draft and edit specification sections and check specifications against drawings and the project basis of design.
  • Perform automated QA/QC checks on drawing sets and markups, including consistency checks across disciplines.
  • Support verification of engineering calculations and equipment schedules.
  • Generate basis-of-design narratives, design reports, and meeting summaries from project inputs.
  • Support RFI and submittal review workflows during construction administration.
  • Support proposal, scope, and fee development.
  • Work alongside Design department leaders to understand priorities and the roadmap, then break them into scoped, buildable deliverables with clear success criteria.
  • Work directly with engineers and designers to understand workflows, pain points, and opportunities for AI to reduce effort without compromising quality.
  • Provide Design leadership with practical input on feasibility, effort, and tradeoffs, and recommend roadmap adjustments based on field learnings.
  • Represent the Design department’s perspective within AI2IO, communicating MEP consulting realities such as professional liability, QA/QC expectations, project deadlines, and fee constraints.
  • Design solutions with human review built in so engineers remain in control of and accountable for engineering judgment and deliverables.
  • Test tools against real project data and known-correct results before release, and document limitations so users know when not to rely on them.
  • Protect client and project confidentiality in the use, storage, and sharing of data across AI platforms.
  • Train engineers and designers on tools through working sessions, short guides, and office hours.
  • Capture user feedback and platform issues and use them to prioritize improvements.
  • Track adoption, usage, and time saved to demonstrate measurable value, and report progress to Design leadership and AI2IO.
  • Surface platform gaps, governance concerns, and feature requests to the AI Enablement Program Manager based on field observations.
  • Document solutions, prompts, and workflows so they can be supported, reused, and scaled across teams.
  • Partner with the AI Enablement Program Manager to convert successful solutions into reusable patterns, case studies, and training materials.
  • Stay current on AI advancements, industry tools, and best practices through ongoing learning, vendor evaluations, and industry engagement, and bring practical opportunities to Design leadership.
  • Complete assigned tasks and deliverables on time and on budget.
  • Perform other related duties as assigned.

Desired Qualifications

  • Experience with the Revit API, Dynamo, or pyRevit is strongly preferred.
  • Familiarity with the Microsoft ecosystem, including SharePoint, Teams, Power Automate, Copilot Studio, and Azure AI Foundry, is preferred.
  • Experience building retrieval-augmented generation (RAG) solutions over document libraries is a plus.
  • Data center or mission critical design experience is preferred.
  • A bachelor’s degree in Mechanical, Electrical, or Architectural Engineering, or a related discipline, is a plus; EIT or PE licensure is also a plus but is not required.

About the Company

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