About the role
Job Title: AI Platform Architect
Reports to: Enterprise AI Architect
Our Purpose
TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are challenged to innovate and learn something new every day.
We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.
What You Will Do
As an AI Platform Architect I at Teradyne, you will help shape how AI is architected, integrated, and governed across the enterprise, spanning AI agent and MCP infrastructure, platform and connector integration, AI governance and risk processes, and enterprise AI literacy. Reporting to the Enterprise AI Architect, you will translate our enterprise AI strategy into concrete architecture patterns, deployment standards, and governance practices, primarily across Azure Foundry, Microsoft Copilot Studio and Copilot Cowork, Snowflake Cortex AI, and Claude.
This is a hands-on technical, architecture-focused role. You will define reusable patterns for deploying AI agents, standardize MCP server design and CI/CD pipelines, AI platform configuration, and set up authentication and authorization middleware for AI agents and services. You will also contribute to the enterprise AI gateway and connector strategy, support AI governance and risk-review processes, and help drive enterprise AI literacy, ensuring AI initiatives scale securely, consistently, and responsibly.
Key Responsibilities
AI Platform & Environment Enablement
Manage platform settings, integrations, and resource allocations to ensure optimal performance and cost-efficiency for development teams
Set up and maintain authentication/authorization middleware for AI agents and services, partnering with the team that owns enterprise identity/access management
Standardize Model Context Protocol (MCP) server design, deployment templates, and infrastructure-as-code patterns
Design and own CI/CD pipelines for AI agent, MCP, and/or AI model deployments (GitHub Actions or Azure DevOps)
Business Outcome:
Provide well-configured, secure, and efficient AI platform environments that enable teams to build and deploy AI solutions reliably.
AI Solution Development
Define architecture patterns and standards for deploying AI agents across the enterprise, primarily on Azure Foundry, Microsoft Copilot / Copilot Studio / Copilot Cowork, Snowflake Cortex AI, and Claude
Establish and document reusable playbooks and modular workflows for agentic AI development, ensuring rapid adoption and consistency across teams leveraging both no-code and programmatic development environments
Architect Retrieval-Augmented Generation (RAG) and agent infrastructure on cloud AI development platforms
Contribute to the design and maintenance of the enterprise AI gateway, including the MCP registry, LLM traffic routing, observability, rate limiting, data redaction, and access control
Contribute to the enterprise connector/integration strategy connecting AI tools to core business systems
Lead architecture reviews for AI agent and enterprise copilot tooling deployments
Business Outcome:
Deliver well-architected, reusable AI solutions that accelerate adoption and demonstrate the value of enterprise AI investment.
AI Governance, Security, and Observability
Contribute to AI governance and risk-review processes, including evaluating new LLMs before adoption and reviewing AI tool and connector requests
Partner with security, legal, and compliance teams to help shape AI risk frameworks, policy, and data governance standards
Contribute to enterprise AI literacy/training tracking and reporting
Business Outcome:
Strengthen AI governance and risk posture while building enterprise-wide AI literacy and capability.
Required Qualifications
Experience: 2–5 years of experience in AI/ML or platform engineering, with hands-on experience deploying AI systems in an enterprise environment
Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
Technical Skills:
Required hands-on experience with Microsoft Azure AI Foundry
Additional experience with Microsoft Copilot Studio, Copilot Cowork, Snowflake Cortex AI, and Claude is ideal
Proficiency in Python and SQL
Hands-on experience building and deploying AI Agents and MCP Servers
Experience designing CI/CD pipelines using GitHub Actions or Azure DevOps
Experience with Infrastructure as Code
Some hands-on experience setting up authentication/authorization
Experience building custom RAG pipelines
Familiarity with AI governance/risk frameworks
Understanding of API/connector integration patterns for enterprise systems
Soft Skills:
Strong collaboration and communication skills, with the ability to work across technical and business teams
Analytical mindset with a focus on delivering measurable business outcomes
Comfortable contributing to governance and security review processes
Why Join Teradyne?
At Teradyne, we are committed to innovation, operational excellence, and empowering our teams to deliver cutting-edge AI solutions that drive business value. As an AI Platform Architect I, you will have the opportunity to work on transformative projects, collaborate with talented professionals, and shape the future of AI at Teradyne. Join us and be part of a team that is redefining what's possible with AI.
Originally posted on Himalayas