Develop and support Murex MX.3 configurations, integrations, and Java services across the front-to-back trade lifecycle, applying strong capital markets knowledge and test-driven engineering practices.
Domain Expert in Residence
📜 Description
- Specify real-world AEC tasks for AI agents, including drawing reviews, code compliance, RFIs, submittals, and QA/QC.
- Create and label gold-standard datasets from project drawings, specifications, RFIs, and submittals.
- Design evaluation rubrics covering severity, discipline, correctness, and usefulness.
- Co-design customer workflows and test agents against project scenarios and common failure modes.
- Translate AEC practice into scalable AI systems with product, ML, and engineering teams.
🛠️ Requirements
- Experience with QA/QC processes or design reviews
- Familiarity with building codes (IBC, ADA, NFPA, local codes)
- Experience writing standards, checklists, or internal review frameworks
- Interest in product development
✨ Benefits
- Competitive compensation based on experience
- Equity for full-time roles
- Flexible part-time options for specialists
Full job description
About Nomic
Nomic builds domain-specific AI agents for the built world — helping Architecture, Engineering, and Construction (AEC) teams across tasks like drawing reviews, takeoffs, code compliance, RFIs, submittals, specs, QA/QC, coordination, and project documentation.
Our goal is to build AI systems that reflect how AEC work is actually done in practice - grounded in real workflows, real constraints, and real project complexity.
About the Role
We’re launching a Domain Experts in Residence (DEIR) program to embed experienced AEC practitioners directly into how our AI agents and workflows are designed, evaluated, and shipped.
This is not a traditional advisory role. As a Domain Expert in Residence, you’ll be hands-on in defining real-world AEC tasks, building datasets, and shaping evaluation criteria that determine how our agents perform across the project lifecycle.
This role is ideal for practitioners who want to shape the future of tools used by their profession.
What You’ll Do
Define real-world AEC task specifications for AI agents (e.g., drawing reviews, code compliance, RFIs, submittals, spec review, QA/QC, coordination)
Create and label gold-standard datasets from real project artifacts (drawings, specs, RFIs, submittals)
Design evaluation rubrics for agent outputs (severity, discipline, correctness, usefulness)
Co-design default workflows that ship to customers
Pressure-test agents against real-world project scenarios and common failure modes
Partner closely with product, ML, and engineering teams to translate domain practice into scalable AI systems
Who You Are
6+ years of professional experience in one or more of:
Architecture
Structural Engineering
MEP Engineering
Construction / Project Management
QA/QC or Code Compliance
Deep familiarity with real AEC workflows and project deliverables
Comfortable articulating how work is actually done in practice
Curious about AI tools and automation (no ML background required)
Motivated to shape the future of AEC tooling
Nice to Have
Experience with QA/QC processes or design reviews
Familiarity with building codes (IBC, ADA, NFPA, local codes)
Experience writing standards, checklists, or internal review frameworks
Interest in product development
Why This Role Is Different
You’ll help define how AI supports real AEC workflows
Your expertise will directly shape products used by real firms
You’ll work closely with product and ML teams
You’ll influence the next generation of tools for your profession
Compensation
Competitive compensation based on experience
Equity for full-time roles
Flexible part-time options for specialists
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