Senior Engineering AI / Advisory Lead

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.