Metric Tree Labs
Website:
metrictreelabs.com
Job details:
Principal AI Solutions Architect – CAD, PLM & Engineering AutomationEngineering AI | Design Automation | Product Development | Generative AIAbout the Role
We are looking for an experienced Principal AI Solutions Architect to lead the development of AI-powered engineering and design automation solutions across our product development lifecycle.
This is NOT a generic Generative AI or chatbot role.
We are specifically looking for someone who has built software, automation, or AI solutions around CAD, PLM, engineering design, manufacturing, product development, technical documentation, or engineering data.
The ideal candidate combines deep knowledge of engineering systems with hands-on expertise in modern AI technologies including LLMs, Computer Vision, AI Agents, RAG, and workflow automation.
You will work closely with engineering, product development, manufacturing, IT, and business teams to design AI solutions that transform engineering workflows—from CAD models to assembly instructions, technical manuals, product visualization, engineering knowledge assistants, and intelligent automation.
Please Apply Only If
You have hands-on experience in at least one of the following domains:
- CAD Automation
- Product Lifecycle Management (PLM)
- Product Engineering
- Mechanical Engineering Software
- Manufacturing Engineering
- Engineering Documentation
- Technical Publications
- Engineering Data Management
- Design Automation
Candidates with experience limited to ChatGPT applications, AI chatbots, generic LLM implementations, or enterprise AI without engineering/CAD domain expertise are unlikely to be a fit for this role.
Key ResponsibilitiesAI Strategy & Solution Architecture
- Define the AI architecture for engineering and product development workflows.
- Identify high-value AI use cases across engineering, manufacturing, design, and documentation.
- Build the roadmap from Proof of Concept to enterprise-scale production deployment.
- Evaluate AI platforms, LLMs, Computer Vision models, Agentic AI frameworks, and engineering AI platforms.
- Design secure, scalable integrations with enterprise engineering systems.
Engineering AI & Design Automation
Build AI-powered solutions for use cases including:
- CAD-to-Assembly Instructions
- CAD-to-Technical Manuals
- CAD Metadata Extraction
- BOM Intelligence
- Engineering Drawing Interpretation
- STEP File Processing
- Engineering Knowledge Assistants
- Product Documentation Generation
- AI-assisted Product Configuration
- Automated Product Visualization
- Product Image Generation
- Engineering Search using RAG
- Design Variant Generation
- Engineering Change Impact Analysis
Hands-on AI Development
- Develop AI prototypes using Python and modern AI frameworks.
- Build AI Agents and multi-agent workflows.
- Design prompt engineering pipelines.
- Build Retrieval-Augmented Generation (RAG) systems.
- Develop Computer Vision pipelines for engineering drawings and CAD assets.
- Process structured and unstructured engineering data.
- Work with CAD models, engineering drawings, BOMs, specifications, manuals, and technical documents.
- Collaborate with software engineering teams to productionize AI solutions.
Engineering Workflow Transformation
Partner with:
- Mechanical Engineering
- Product Engineering
- Industrial Design
- Manufacturing Engineering
- Technical Publications
- Packaging Engineering
- Product Marketing
- Operations
to automate engineering workflows using AI.
Enterprise Integration
Integrate AI capabilities with:
- CAD Platforms
- PLM Systems
- PDM Systems
- ERP
- Document Management Systems
- Knowledge Repositories
- Product Information Management (PIM)
- Digital Asset Management (DAM)
using secure API-first architectures.
Governance & Quality
- Define AI governance standards for engineering data.
- Protect CAD files and product intellectual property.
- Build validation workflows to ensure technical accuracy.
- Implement hallucination controls.
- Establish Human-in-the-Loop approval workflows.
- Ensure traceability and auditability of AI-generated engineering content.
Vendor Evaluation
- Evaluate engineering AI vendors.
- Conduct technical proof-of-concepts.
- Recommend Build vs. Buy decisions.
- Lead technical vendor assessments.
Required Qualifications
- 8+ years of experience in Software Engineering, Engineering Systems, Product Engineering, Manufacturing Technology, Enterprise Applications, or AI.
- Proven experience building software solutions around engineering design workflows.
- Strong understanding of CAD, PLM, PDM, BOMs, engineering drawings, or technical documentation.
- Hands-on experience with modern AI technologies including:
- Large Language Models (LLMs)
- Generative AI
- Computer Vision
- AI Agents
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Strong Python development experience.
- Experience integrating enterprise systems using APIs.
- Experience taking AI solutions from prototype to production.
- Excellent communication and stakeholder management skills.
Preferred Experience
Hands-on experience with one or more of the following:
CAD Platforms
- PTC Creo
- SolidWorks
- Autodesk Inventor
- AutoCAD
- Siemens NX
- CATIA
- Onshape
PLM Platforms
- Windchill
- Teamcenter
- ENOVIA
- Aras PLM
- Autodesk Vault
Engineering Data
Experience working with:
- STEP
- IGES
- STL
- DWG
- DXF
- OBJ
- CAD Assemblies
- Engineering Drawings
- BOM Structures
- Engineering Specifications
- Technical Manuals
Technical SkillsAI & Machine Learning
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents
- Prompt Engineering
- Computer Vision
- Generative AI
- LangChain
- LlamaIndex
- OpenAI / Azure OpenAI
- AWS Bedrock
- Google Vertex AI
Programming
- Python
- REST APIs
- JavaScript / TypeScript
- Automation
- Scripting
Cloud
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
Data
- SQL
- Vector Databases
- Metadata Extraction
- Document Parsing
- Embeddings
Enterprise Systems
- CAD
- PLM
- PDM
- ERP
- PIM
- DAM
- Technical Documentation Systems
Ideal Candidate Background
Candidates with experience in one or more of the following environments are strongly preferred:
- CAD Software Companies
- PLM Software Vendors
- Industrial Manufacturing Organizations
- Product Engineering Companies
- Mechanical Design Teams
- Engineering R&D Organizations
- Manufacturing Technology Companies
- Engineering Services Firms
- Industrial Automation Companies
- Digital Engineering Consulting Firms
What Success Looks Like
Within your first 12 months, you will have:
- Delivered production-ready AI solutions for engineering and product development workflows.
- Automated key engineering documentation and design processes.
- Built scalable AI services integrated with CAD and PLM ecosystems.
- Enabled engineering teams to accelerate product development using AI.
- Established the technical foundation for an enterprise-wide Engineering AI platform.
Click on Apply to know more.