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AI Platform Architect

Teradyne
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Hybrid (Remote, India)full-timePosted 4d ago

About the role

AI Platform Architect I at Teradyne responsible for shaping AI architecture, integration, and governance across the enterprise, focusing on AI agents, MCP infrastructure, platform and connector integration, governance, and enterprise AI literacy.

Responsibilities

  • 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)
  • 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
  • Architect Retrieval-Augmented Generation (RAG) and agent infrastructure on cloud AI development platforms
  • Contribute to 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
  • 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 shape AI risk frameworks, policy, and data governance standards
  • Contribute to enterprise AI literacy/training tracking and reporting
  • Support AI governance, security, and observability initiatives to strengthen governance and risk posture while enabling enterprise-wide AI literacy

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: Hands-on experience with Microsoft Azure AI Foundry; 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; Analytical mindset with a focus on delivering measurable business outcomes; Comfortable contributing to governance and security review processes

Skills

Required:Azure AI FoundryPythonSQLMCP ServerCI/CDInfrastructure as CodeCollaborationCommunicationGovernance
Nice to have:Copilot Studio / Copilot CoworkSnowflake Cortex AIClaudeAuthentication/AuthorizationRAG pipelinesAI governance/risk frameworksAPI/Connector integration
Last updated Oct 22, 2026. Interested? Apply on the company site.

About Teradyne

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