Senior AI Platform Architect (Teradyne, North Reading)

Teradyne•North Reading, MA

10d•$139,900 - $223,900•Onsite

About The Position

As an AI Platform Architect II at Teradyne, you will be a pivotal leader at the forefront of our AI transformation. Reporting to the Enterprise AI Architect, your primary responsibility will be to design and evangelize a cohesive, enterprise-wide AI and Data architecture. This involves creating the blueprint for a scalable and secure ecosystem that leverages our investments in Microsoft 365 & Copilot, Azure Foundry, Google Vertex AI, and Snowflake Cortex AI. You will guide the selection of AI tools, define the data integration strategy, and establish reusable patterns for agentic development to mature skills across the organization. Beyond the technical architecture, you will be a key change agent, responsible for embedding AI into the fabric of our business. Your role is crucial in bridging the gap between strategy and execution by fostering an AI-ready culture, building institutional literacy, and guiding the company through the deep, structural shifts in how we work and make decisions. You will ensure our people, processes, and technology are aligned to unlock the full promise of AI and drive a sustainable competitive advantage.

Requirements

6-8 years in Information Technology including Enterprise Architecture and AI/ML/GenAI Engineering.
Proven experience in designing and implementing large-scale, enterprise-wide AI solutions.
Bachelor’s Degree in Computer Science, Information Systems, Engineering, or a related field required
Deep understanding of AI and machine learning concepts, including generative AI, large language models (LLMs), and MLOps.
Expertise in designing and building solutions on cloud platforms, with a strong preference for Microsoft Azure and a working knowledge of Google Cloud Platform.
Hands-on experience with and a deep architectural understanding of our core AI and data platforms: Microsoft 365 Copilot, Microsoft Copilot Studio, Azure AI (including the future Azure AI Foundry), Google Vertex AI, and Snowflake Cortex AI.
Strong knowledge of data architecture, data governance, and data security best practices.
Familiarity with Infrastructure as Code (IaC) and CI/CD principles.
Exceptional leadership and communication skills, with the ability to articulate a clear vision and influence stakeholders at all levels of the organization.
Analytical mindset with a focus on delivering measurable business outcomes.
Strong strategic thinking and business acumen, with the ability to connect technology solutions to business value.
A collaborative and mentoring mindset, with a passion for upskilling teams and fostering a culture of innovation.

Responsibilities

Architect and operationalize the enterprise AI strategy by developing a comprehensive architectural blueprint and component-level roadmap that unifies our AI and data ecosystem.
Lead the design of a unified AI ecosystem that integrates our core platforms, ensuring seamless data flow and interoperability between our AI Platforms, Data, and Enterprise SaaS solutions.
Establish and champion architectural standards, reusable MLOps & LLMOps patterns, and best practices for AI development to ensure consistency, scalability, and efficiency.
Architect and lead the strategy for a centralized Model Context Protocol (MCP) Server, creating a unified gateway for secure, observable, and governed interactions between AI agents and all enterprise tools, data sources, and services.
Evaluate emerging AI technologies, frameworks, and methodologies, making strategic recommendations for their adoption and integration into our enterprise architecture.
As a core member of the AI Transformation Office, drive the change management strategy to accelerate the adoption of AI technologies and cultivate a culture of innovation.
Mentor and upskill teams in agentic AI design, MLOps & LLMOps practices, and solution architecture, fostering a culture of innovation and continuous learning.
Act as a key advisor to business leaders, helping them to identify and prioritize high-impact AI use cases and understand the transformative potential of AI for their respective domains.
Lead and facilitate workshops, training programs, documentation, and knowledge-sharing sessions to upskill our workforce and build AI literacy across all business functions.
Partner with CISO to architect and implement a comprehensive AI governance framework that includes policies for data privacy, model risk management, and regulatory compliance.
Ensure that all AI solutions are designed for scalability, reliability, and cost-effectiveness, making strategic decisions on resource allocation and optimization.
Oversee the design of our MLOps and LLMOps strategy, ensuring that we have the right processes and tools in place to manage the entire lifecycle of our AI models & agents, from development to deployment and monitoring.