Job Description
The 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
- Bachelor's degree in engineering and master's 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 as LangGraph, Google ADK, AutoGen, and the Model 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
