Teradyne
Opportunity Overview
Reporting to the Head of Enterprise Architecture and Data, the Enterprise AI Architect is a key contributor shaping Teradyne’s AI landscape. The role sets and executes the enterprise AI strategy, promotes adoption and integration of AI and GenAI technologies, and ensures AI is embedded in both business processes and technical platforms.
The architect collaborates across business and technical teams to maximize AI’s impact, leveraging expertise to evaluate solution designs, align business capabilities, and develop a cloud-native, flexible, and agile future-state architecture.
Key Responsibilities
Guide formulation and evolution of Teradyne’s enterprise AI strategy, aligning with business and technology objectives to drive measurable value and market advantage.
Identify, prioritize, and evangelize AI opportunities across the company, including automation, forecasting, supply chain, field service, finance, and more.
Stay ahead of industry trends, integrating emerging AI technologies and best practices into Teradyne’s roadmap.
Architect, implement, and oversee scalable, secure, and maintainable AI solutions, ensuring seamless integration with enterprise platforms (SAP SuccessFactors, Oracle, ServiceNow, Salesforce, Siemens Teamcenter, etc.).
Advance proof‑of‑concept projects and pilots, working hands‑on with teams to validate and scale GenAI and agentic solutions.
Facilitate onboarding and adoption of 3rd‑party LLM tools (Enterprise ChatGPT, Google Agentspace, Cursor, etc.), integrating them securely and efficiently into the enterprise.
Set architecture requirements and guide the design for AI‑ready data pipelines using Snowflake, Informatica, and Microsoft Fabric, ensuring high‑quality, governed, and accessible data.
Architect and design for multi‑cloud AI deployments across Azure, AWS, and GCP, leveraging cloud‑native tools and best practices.
Collaborate with the CIO, CISO, Head of Engineering, and Chief AI Officer to facilitate robust AI governance frameworks, policies, and best practices to ensure ethical, secure, and compliant AI development and deployment.
Provide a framework to continuously monitor and optimize AI models and solutions for performance, accuracy, and business impact.
Foster cross‑functional collaboration with data scientists, engineers, IT, business heads, and product teams to drive AI adoption and innovation, aligning AI strategies and driving widespread adoption.
Partner with the Enterprise Data Governance and Data Product teams to ensure delivery of high‑quality, AI‑ready data.
Key Qualifications
10+ years in technology, with 5+ years delivering AI architecture solutions.
Expertise with Snowflake, Databricks, Microsoft AI technologies (Copilot, Fabric, Power BI, M365), and multi‑cloud AI deployments (Azure, AWS, GCP).
Minimum of 8 years of hands‑on experience with cloud AI tools (AWS, Azure, GCP) and scalable data platforms.
Minimum of 3 years of experience developing architecture blueprints, strategies, and roadmaps.
Proven ability to onboard and guide the adoption of 3rd‑party LLM tools (Enterprise ChatGPT, Google Agentspace).
Strong knowledge of MLOps, DataOps, and/or enterprise data governance.
Excellent communication skills, able to influence executives and mentor technical teams.
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
Deep understanding of new and emerging technology trends, and the practical application of existing, new, and emerging technologies to new and evolving business and operating models.
Deep understanding of product management, agile values, and development methodologies.
Ability to build trust and respect as a person who can influence and persuade business and IT department heads and development teams.
Analytic mindset that prioritizes enterprise‑wide needs and remains unbiased toward any specific technology or vendor choice.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Industry Semiconductor Manufacturing
Locations Cambridge, MA | Boston, MA | Andover, MA | Burlington, MA | Lowell, MA
EEO Statement Teradyne is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive work environment for all employees.
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The architect collaborates across business and technical teams to maximize AI’s impact, leveraging expertise to evaluate solution designs, align business capabilities, and develop a cloud-native, flexible, and agile future-state architecture.
Key Responsibilities
Guide formulation and evolution of Teradyne’s enterprise AI strategy, aligning with business and technology objectives to drive measurable value and market advantage.
Identify, prioritize, and evangelize AI opportunities across the company, including automation, forecasting, supply chain, field service, finance, and more.
Stay ahead of industry trends, integrating emerging AI technologies and best practices into Teradyne’s roadmap.
Architect, implement, and oversee scalable, secure, and maintainable AI solutions, ensuring seamless integration with enterprise platforms (SAP SuccessFactors, Oracle, ServiceNow, Salesforce, Siemens Teamcenter, etc.).
Advance proof‑of‑concept projects and pilots, working hands‑on with teams to validate and scale GenAI and agentic solutions.
Facilitate onboarding and adoption of 3rd‑party LLM tools (Enterprise ChatGPT, Google Agentspace, Cursor, etc.), integrating them securely and efficiently into the enterprise.
Set architecture requirements and guide the design for AI‑ready data pipelines using Snowflake, Informatica, and Microsoft Fabric, ensuring high‑quality, governed, and accessible data.
Architect and design for multi‑cloud AI deployments across Azure, AWS, and GCP, leveraging cloud‑native tools and best practices.
Collaborate with the CIO, CISO, Head of Engineering, and Chief AI Officer to facilitate robust AI governance frameworks, policies, and best practices to ensure ethical, secure, and compliant AI development and deployment.
Provide a framework to continuously monitor and optimize AI models and solutions for performance, accuracy, and business impact.
Foster cross‑functional collaboration with data scientists, engineers, IT, business heads, and product teams to drive AI adoption and innovation, aligning AI strategies and driving widespread adoption.
Partner with the Enterprise Data Governance and Data Product teams to ensure delivery of high‑quality, AI‑ready data.
Key Qualifications
10+ years in technology, with 5+ years delivering AI architecture solutions.
Expertise with Snowflake, Databricks, Microsoft AI technologies (Copilot, Fabric, Power BI, M365), and multi‑cloud AI deployments (Azure, AWS, GCP).
Minimum of 8 years of hands‑on experience with cloud AI tools (AWS, Azure, GCP) and scalable data platforms.
Minimum of 3 years of experience developing architecture blueprints, strategies, and roadmaps.
Proven ability to onboard and guide the adoption of 3rd‑party LLM tools (Enterprise ChatGPT, Google Agentspace).
Strong knowledge of MLOps, DataOps, and/or enterprise data governance.
Excellent communication skills, able to influence executives and mentor technical teams.
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
Deep understanding of new and emerging technology trends, and the practical application of existing, new, and emerging technologies to new and evolving business and operating models.
Deep understanding of product management, agile values, and development methodologies.
Ability to build trust and respect as a person who can influence and persuade business and IT department heads and development teams.
Analytic mindset that prioritizes enterprise‑wide needs and remains unbiased toward any specific technology or vendor choice.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Industry Semiconductor Manufacturing
Locations Cambridge, MA | Boston, MA | Andover, MA | Burlington, MA | Lowell, MA
EEO Statement Teradyne is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive work environment for all employees.
#J-18808-Ljbffr