Senior Engineering AI / Advisory Lead

Tek Analytics, LLC.; Chicago (IL); On-site; USD 180,000 - 240,000; Full time

Job summary

Tek Analytics, LLC. is seeking a Lead Engineering AI advisor to guide advisory engagements across industrial engineering, manufacturing, and asset-intensive environments.

You will own portfolio discovery, maturity assessment, technical architecture, and AI/ML solution development direction, including integration with PLM, ERP, MES, EAM, and related data systems. The role requires deep expertise in GenAI, LLMs, computer vision, and deployment architectures, with emphasis on production readiness,

Qualifications

• Bachelor's or Master's in Engineering, CS, Data Science, or related field.
• 16-20+ years of relevant technology experience in AI/ML, industrial digital solutions, or solution architecture.

Responsibilities

• Lead discovery workshops and assess Engineering AI solutions, prototypes, production apps, and roadmaps.
• Define target-state architectures, roadmaps, priorities, and governance.
• Guide AI/ML approaches, data pipelines, and integration patterns for industrial platforms.
• Lead technical design reviews, model validation, integration testing, and deployment readiness.
• Establish production monitoring, maintenance, and continuous optimization practices.

Skills

AI/ML architecture

GenAI & LLMs

Industrial engineering

AI delivery leadership

Stakeholder management

MLOps

Solution architecture

Computer vision

Education

Engineering / CS degree

Tools

AVEVA

Hexagon

AutoCAD

CAD/DXF

Job description

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.