DescriptionThe primary objective of this role is to stay at the forefront of AI innovation by evaluating piloting and deploying AI solutions. The specialist serves as a strategic advisor and hands-on innovator influencing architecture engineering and product teams to integrate AI capabilities in scalable and responsible ways. This includes defining technical blueprints building AI proof-of-concepts and supporting adoption through alignment with IT and enterprise architecture.
Responsibilities- Develop the roadmap for AI deployment including Generative and Agentic AI solutions aligning technological capabilities with long-term business outcomes and engineering efficiency improvements.
- Develop frameworks Architect and oversee the deployment of multi-agent systems (MAS) that transform end-to-end business processes within the connected ecosystem
- Design and guide the development of AI capabilities and innovation pilots translating business goals into AI-enabled solutions.
- Define architectural blueprints for integrating AI technologies into PLM IT systems and platforms ensuring security scalability and alignment with enterprise standards.
- Drive initiatives for AI prototyping proof-of-concepts (PoCs) and production readiness assessments.
- Act as a center of excellence for AI within the Manufacturing Engineering organization driving awareness knowledge sharing and standardization.
Qualifications- Bachelors degree in engineering and masters in computer science AI/ML/ Data Science or related fields is preferred.
- 10 years of work experience with at least 25 years dedicated to AI Generative AI and production-scale autonomous systems
- Industry certifications/ advanced credentials in machine learning or cloud-based AI platforms (e.g. AWS Certified Machine Learning Specialty Google Cloud AI Engineer) are advantageous.
- Proven mastery of frameworks such asLangGraph Google ADK AutoGen and theModel Context Protocol (MCP)for tool orchestration
- Excellent track record of evaluating piloting and operationalizing AI solutions in enterprise environments.
- Experience working across multiple industries and large-scale Engineering organizations
Required Experience:
Staff IC
DescriptionThe primary objective of this role is to stay at the forefront of AI innovation by evaluating piloting and deploying AI solutions. The specialist serves as a strategic advisor and hands-on innovator influencing architecture engineering and product teams to integrate AI capabilities in sca...
DescriptionThe primary objective of this role is to stay at the forefront of AI innovation by evaluating piloting and deploying AI solutions. The specialist serves as a strategic advisor and hands-on innovator influencing architecture engineering and product teams to integrate AI capabilities in scalable and responsible ways. This includes defining technical blueprints building AI proof-of-concepts and supporting adoption through alignment with IT and enterprise architecture.
Responsibilities- Develop the roadmap for AI deployment including Generative and Agentic AI solutions aligning technological capabilities with long-term business outcomes and engineering efficiency improvements.
- Develop frameworks Architect and oversee the deployment of multi-agent systems (MAS) that transform end-to-end business processes within the connected ecosystem
- Design and guide the development of AI capabilities and innovation pilots translating business goals into AI-enabled solutions.
- Define architectural blueprints for integrating AI technologies into PLM IT systems and platforms ensuring security scalability and alignment with enterprise standards.
- Drive initiatives for AI prototyping proof-of-concepts (PoCs) and production readiness assessments.
- Act as a center of excellence for AI within the Manufacturing Engineering organization driving awareness knowledge sharing and standardization.
Qualifications- Bachelors degree in engineering and masters in computer science AI/ML/ Data Science or related fields is preferred.
- 10 years of work experience with at least 25 years dedicated to AI Generative AI and production-scale autonomous systems
- Industry certifications/ advanced credentials in machine learning or cloud-based AI platforms (e.g. AWS Certified Machine Learning Specialty Google Cloud AI Engineer) are advantageous.
- Proven mastery of frameworks such asLangGraph Google ADK AutoGen and theModel Context Protocol (MCP)for tool orchestration
- Excellent track record of evaluating piloting and operationalizing AI solutions in enterprise environments.
- Experience working across multiple industries and large-scale Engineering organizations
Required Experience:
Staff IC
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