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Salary
≈ $19k – $49k per year (Estimated)
Location
In office (Lapu-Lapu)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on Oct 20, 2026.

Overview
Company
Impact
Profile match
Teradyne is a manufacturer of automated test equipment for semiconductors and electronics. Its testers validate chips before they ship into consumer and automotive products, the company also owns collaborative robotics businesses, and it hires engineers, planners, sales managers and field specialists in the United States and Asia. The company is headquartered in North Reading, Massachusetts, United States.
Backed by Punakaiki Fund

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 supported 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.

Opportunity Overview

The AI Transformation team, part of the Chief AI Officer’s organization, is accelerating the deployment of AI-augmented workflows across the entire organization. Our mission is to augment employee capabilities and embed intelligence into the most critical workflows that drive our business. We’re seeking a Forward Deployed Engineer, AI Enablement who approaches every challenge by first considering what modern AI tools can solve, focusing on rapid prototyping, validation, and deployment of AI solutions where your success will directly impact business metrics.

  • Design and deploy AI-augmented workflows using modern platforms (Microsoft Copilot Studio/Foundry, LangChain, LlamaIndex, and similar frameworks)

  • Build natural language interfaces, conversational AI systems, and AI-enabled applications from user interfaces to backend systems

  • Collaborate with stakeholders across sales, engineering, operations, finance, and product teams to translate AI capabilities into measurable business value

  • Lead AI solutions from concept to production with focus on built-in quality, establishing baselines and tracking metrics to demonstrate business outcomes

  • Partner with business teams to rapidly diagnose workflow bottlenecks and architect AI solutions that stakeholders can sustain independently

  • Contribute to continuous improvement culture and team collaboration

All About You

We seek individuals who share our passion and determination. Our commitment to customer success drives us to go the extra mile. If you’re ready to join us in this mission, take a closer look at the minimum criteria for the position.

  • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or related technical field

  • 3-5 years of software engineering experience

  • Fluency in AI-native development tools (Cursor, OpenAI Codex, Claude Code, or similar)

  • Hands-on experience with modern AI platforms or frameworks (Microsoft Copilot Studio/Foundry, LangChain, LlamaIndex, or similar)

  • Strong full-stack development skills with modern programming languages and frameworks

  • Excellent communication skills in English, both written and spoken

  • Intellectual curiosity across technical and business domains, blended with outcome-driven mindset

  • Business outcome orientation with ability to connect technical work to measurable metrics

Bonus Points For

  • Master’s degree in Computer Science, Machine Learning, or related field

  • Experience with Microsoft ecosystem tools like Power Platform, Graph API, or Azure AI Search

  • Fluency in AI CLI tools such as Claude Code, Codex CLI, or Gemini CLI; experience with compound engineering features (Cursor rules, AI agent subflows, or similar agentic workflows)

  • Hands-on experience with agentic AI frameworks (OpenClaw, LangGraph, etc.), local model inference (Ollama), and MCP

  • Backend expertise in data pipelines, cloud infrastructure, DevOps, or MLOps

  • Background in prompt engineering, RAG architectures, vector databases, or LLM fine-tuning

  • Experience with commercial enablement tools (sales copilots, CRM AI workflows including Salesforce, marketing automation, support bots)

  • Understanding of enterprise AI considerations (security, compliance, data governance)

  • Experience measuring and optimizing AI system quality (accuracy, relevance, latency, cost) and AI productivity impact across SDLC phases

  • Experience in forward-deployed or customer-embedded engineering roles, solutions engineering, or technical consulting

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