We are a diverse group of talented people committed to creating solutions to problems and making the world a better place. We enhance and deliver both mechanical and electrified solutions that bring efficiency and sustainability to new heights. Founded in 1979, Litens has a proud history of being an innovative and highly respected company specializing in powertrain system engineering and component supply. Our history includes numerous achievements, many of which have been recognized through prestigious awards from our customers.
Experience a fulfilling and supportive environment where ingenuity is rewarded, collaboration is encouraged, and opportunities are readily available.
Why Join Litens?Join Litens Information Technology team as an AI Application Manager. The AI Application Manager leads the strategy, development, and deployment of AI solutions across manufacturing, engineering, and quality functions. Operating within a high-volume automotive Tier 1 environment, this role ensures AI initiatives enhance product quality, accelerate development cycles, support engineering systems, and meet OEM expectations and IATF 16949 standards .
At Litens, you can make an impact. We’ve purposefully cultivated a supportive and flexible environment that gives everyone the opportunity to succeed. Litens offers a competitive and people-first approach to compensation and benefits, and we are committed to provide balanced employment and advancement opportunities for everyone.
Our diversity is our source of strength. At Litens, we are committed to equal employment opportunity, and we value and welcome diversity. We respect employees’ rights for a protected and respectful workplace.



Accommodations for disabilities in relation to the job selection process are available upon request.
What will you do?
Develop an AI roadmap aligned with OEM requirements, engineering needs, and plant KPIs.
Identify high value use cases across product development, validation, manufacturing, and supply chain.
Evaluate emerging AI technologies relevant to automotive quality, traceability, and engineering workflows.
AI Solution Development & Deployment
Lead end to end development of AI applications including:
Computer vision for defect detection, weld inspection, assembly verification, and surface quality.
Predictive maintenance for presses, robots, injection molding machines, and other critical assets.
AI driven process optimization for cycle time, scrap reduction, and energy efficiency.
Demand forecasting and inventory optimization supporting JIT/JIS requirements.
Oversee data acquisition from sensors, PLCs, MES, SCADA, and engineering systems.
Ensure seamless integration of AI tools with ERP, MES, QMS, PLM, CAD/CAE, and traceability platforms.
Collaborate with product engineering teams to embed AI into the product development lifecycle.
Support engineering systems such as:
PLM (Product Lifecycle Management)
CAD/CAE tools (e.G., CATIA, NX, SolidWorks, ANSYS)




Requirements management systems (e.G., DOORS, Jama)
Simulation and digital twin environments
Develop AI models that enhance engineering workflows, including:
Automated design validation and tolerance analysis.
Predictive modelling for material behaviour, durability, and NVH.
AI assisted DFMEA/PFMEA insights and risk prioritization.
Automated document classification, change impact analysis, and engineering data extraction.
Partner with engineering leadership to accelerate APQP and PPAP readiness using AI driven insights.
Ensure engineering data pipelines are structured, governed, and optimized for AI use.
Quality & Compliance
Ensure AI tools support IATF 16949, APQP, PPAP, FMEA, MSA, and OEM specific quality requirements.
Maintain documentation for AI models, validation results, and change control.
Collaborate with quality teams to embed AI into control plans and problem-solving processes.
Operations & Continuous Improvement
Monitor AI system performance and drive continuous improvement cycles.
Establish KPIs for accuracy, uptime, scrap reduction, throughput, and ROI.
Support plant teams with troubleshooting and root cause analysis using AI insights.
Lead training and change management efforts to increase adoption across engineering and production.
Governance, Security & Data Management
Ensure compliance with cybersecurity standards such as TISAX.
Implement responsible AI practices, including transparency, auditability, and model governance.
Maintain documentation for datasets, models, and deployment pipelines.
Cross Fun

📌 Ai Application Manager (Toronto)
🏢 Litens
📍 Toronto