Role Summary
We are looking for a Senior Product Manager to lead AI/ML-driven
product initiatives in the AEC (Architecture, Engineering, and Construction)
and BIM (Building Information Modeling) domain.
The ideal candidate brings a strong blend of product management, AI/ML
expertise, and AEC/BIM domain knowledge, with experience building intelligent
systems that enhance design automation, construction efficiency, and lifecycle
asset management.
You will define and deliver AI-powered capabilities that transform how
buildings and infrastructure are designed, coordinated, built, and operated.
Core Responsibilities
Product Strategy & Roadmap
- Own and drive the
product roadmap for AI/ML-powered BIM and AEC platforms
- Identify high-impact
opportunities to apply AI/ML across design, coordination, construction,
and operations workflows
- Define product
vision for intelligent features such as predictive analytics, generative
design, and automated decision-making
AI/ML Product Development
- Design and
deliver AI-driven capabilities, including:
- Automated clash
detection and resolution
- Generative design
and layout optimization
- Predictive insights
for schedule delays, cost overruns, and risks
- Computer vision
models for site monitoring and progress tracking
- Intelligent
document processing (drawings, RFIs, submittals)
- Translate complex
AI/ML models into scalable, user-facing product features
Data & Platform Capabilities
- Define data
strategies for BIM and construction datasets (models, drawings, IoT, site
data)
- Build and scale:
- Data pipelines for
structured and unstructured AEC data
- Model training,
validation, and deployment frameworks
- Feedback loops for
continuous model improvement
- Ensure
governance, data quality, and compliance across AI systems
Workflow Optimization & Automation
- Enhance AEC
workflows using automation in:
- Model coordination
and validation
- Quantity take-offs
and estimation
- Construction
planning and reporting
- Identify
inefficiencies in AEC processes and apply AI for optimization
Cross-functional Collaboration
- Work closely with
data scientists, ML engineers, BIM specialists, and software engineers
- Partner with
architects, civil engineers, contractors, and project managers to validate
real-world use cases
- Collaborate with
enterprise IT teams to enable integration with ERP, GIS, and project
management systems
Metrics & Performance
- Define and track
KPIs such as:
- Model accuracy and
performance
- Reduction in
project risks and delays
- Improvement in
productivity and cost efficiency
- Adoption of AI-driven features
Requirements
Mandatory Skills / Qualifications
- 10+ years of product
management experience, with exposure to AI/ML-based products and platforms
- Strong domain
experience in AEC, BIM, construction technology, or infrastructure
platforms
- Proven ability to
deliver data-driven and AI-powered products at scale
Technical Expertise
- Strong
understanding of:
- Machine learning
concepts (supervised, unsupervised, deep learning)
- Computer vision and
NLP applications relevant to AEC
- Data engineering
and ML lifecycle (training, deployment, monitoring)
- Familiarity with
BIM technologies and workflows:
- Model coordination,
clash detection, and lifecycle management
- Data formats such
as IFC, RVT, COBie
Domain Knowledge
- Deep
understanding of:
- Design-to-construction
lifecycle
- Project planning,
scheduling, and cost management
- AEC collaboration
workflows and Common Data Environments (CDE)
Execution Skills
- Strong
problem-solving and analytical mindset
- Experience
translating complex technical concepts into customer-centric solutions
- Ability to manage
cross-functional teams and stakeholders
Nice to Have
- Experience with BIM
tools such as Autodesk Revit, Navisworks, BIM 360 / Autodesk Construction
Cloud, Bentley, Trimble
- Exposure to:
- Digital twins and
smart infrastructure
- 4D/5D BIM (schedule
and cost integration)
- IoT and sensor data
integration in construction
- Background in civil
engineering, architecture, construction management, or related fields
- Experience building
AI for real-world physical environments (e.g., construction sites,
infrastructure)
- Familiarity with
cloud platforms (Azure, AWS, GCP) for ML deployment
Success Metrics
- Successful delivery
of AI-driven BIM and AEC product capabilities
- Reduction in project
delays, rework, and cost overruns
- Improved design
quality and coordination efficiency
- Increased adoption
of AI-powered features by AEC stakeholders
- Measurable gains in
productivity and automation across workflows
- Scalable deployment
of ML models across multiple projects or customers
Impact of the Role


