Role Summary
Lead Engineering AI advisory and delivery engagements across industrial engineering, manufacturing, and asset-intensive environments. Own portfolio discovery, solution maturity assessment, technical architecture, AI/ML solution development direction, industrial integration, deployment, and ongoing improvement of Engineering AI solutions.
Key Responsibilities
· Lead discovery workshops and assess existing Engineering AI solutions, prototypes, production applications, and roadmap initiatives.
· Evaluate solution maturity, functional depth, adoption, architecture, AI/ML approaches, data pipelines, integration patterns, and production readiness.
· Identify technical gaps, bottlenecks, improvement opportunities, reusable components, and capability requirements.
· Define target-state architectures, technical roadmaps, implementation priorities, and solution governance.
· Lead technical direction for industrial AI use cases, including predictive maintenance, engineering drawing intelligence, automated BOM extraction, engineering knowledge graphs, 3D model intelligence, digital twins, and AI-powered quality inspection.
· Guide the application of AI/ML, computer vision, GenAI, local LLMs, RAG, and agentic AI to industrial engineering problems.
· Assess and guide solutions involving AVEVA, AutoCAD, Hexagon, DXF, engineering drawings, 3D models, drone/scan data, point clouds, and pipe-routing workflows.
· Define integration approaches across industrial engineering platforms, PLM, ERP, MES, EAM, PLC/SCADA, and industrial data systems.
· Lead technical design reviews, model validation, integration testing, deployment readiness, and resolution of complex technical issues.
· Establish production monitoring, maintenance, model improvement, and continuous optimization practices.
· Identify required specialist skills, delivery capabilities, and reusable engineering AI components; guide technical teams and client stakeholders.
Required Skills
· Strong expertise in AI/ML solution architecture and applied AI, with working knowledge of GenAI, LLMs, RAG, computer vision, and agentic AI.
· Strong understanding of industrial engineering, manufacturing, asset management, or engineering design workflows.
· Experience with industrial engineering software and integration patterns, preferably AVEVA, Hexagon, AutoCAD, or comparable platforms.
· Understanding of engineering data, CAD/DXF, 3D models, engineering BOMs, industrial data pipelines, and enterprise/operational systems.
· Experience assessing model accuracy, robustness, edge cases, scalability, observability, security, and production readiness.
· Knowledge of deployment architecture, MLOps, monitoring, maintenance, and solution lifecycle management.
· Strong technical advisory, architecture, problem-solving, delivery leadership, and stakeholder management capabilities.
Qualifications
· Bachelor's or Master's degree in Engineering, Computer Science, Data Science, or a related discipline.
· 16–20+ years of relevant technology experience, including substantial experience in AI/ML, industrial digital solutions, or solution architecture.
· Demonstrated ownership of technical delivery from discovery and solution design through implementation, deployment, and maintenance.
· Experience leading technical assessments, architecture reviews, and complex industrial or enterprise technology initiatives.
Expected Capabilities
Lead structured discovery and maturity assessments; define technical direction and roadmaps; guide specialized Engineering AI implementations; and own architecture, technical quality, delivery outcomes, and production readiness.
