Technical AI Architect

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.
  
  
  

• 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 2–5 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