AI Enablement Forward Deployed Engineer
Posted 4 days ago
The role in short
Embed with internal engineering teams to build, test, and deploy production AI integrations and agents, ensuring they are documented and handed off for ongoing maintenance.
Our Purpose
TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought 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
As an AI Platform Forward Deployed Engineer, you will work directly with engineering teams across Teradyne to apply an AI platform to their real work. You will turn a team’s workflow into a focused, tested integration, show whether it improves outcomes, and leave the team able to run and extend it without you.
- Learn a partner team’s workflow, constraints, data and access dependencies, current process, success measures, and owner.
- Build and test a focused integration through agreed platform interfaces, with appropriate data and access practices.
- Compare results with a baseline using measures such as usage, quality, task success, effort, latency, cost, or failures.
- Make the integration ready to operate, with tests for main and failure paths, useful telemetry and logs, a troubleshooting runbook, and documentation others can extend.
- Support the integration through its first release, then hand it off with baseline results, an agreed owner, and an escalation path.
Bring recurring integration needs to platform owners as evidence-backed proposals for reusable capabilities.
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.
- Develop, debug, test, and maintain software used by others in at least one general-purpose language, using Git-based workflows (pull requests, code review, automated tests, CI).
- Understand an engineering team’s workflow and turn its constraints into a clear, bounded software integration.
- Integrate services, APIs, SDKs, and developer tools, including authentication and data handling, and diagnose failures using logs, metrics, or traces.
- Verify AI-assisted changes through testing and review, and judge when AI helps and when simpler software fits better.
- Compare results against a baseline, take an integration through its first release with documentation for an agreed owner, and explain tradeoffs to teams in unfamiliar domains.
Preferred Qualifications
- Building AI skills or agents, using model APIs, C#/.NET development, or forward-deployed and developer-tooling work.
- Containers, Kubernetes, cloud infrastructure, observability, or retrieval-enabled systems.
Compensation: The base salary range for this role is $132,100 - $211,400. This range is a good faith estimate, and the amount of base salary will correspond with experience and skill set. This range can also fluctuate depending on demand and location.
Incentive Plan: This job is eligible for discretionary bonus(es) based on financial performance.
Benefits: Teradyne offers a variety of robust health and well-being benefit programs, including medical, dental, vision, Flexible Spending Accounts, retirement savings plans, life and disability insurance, paid vacation & holidays, tuition assistance programs, and more.
Job Segment: Testing, Cloud, .NET, Engineer, Technology, Engineering
Prep for this interview
2 questions likely to come up at Teradyne, each matched to a line in this posting.
- 1Integrations and APIs
They wrote: “Build and test a focused integration through agreed platform interfaces, with appropriate data and access practices.”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 2Cloud, deployment and security
They wrote: “Containers, Kubernetes, cloud infrastructure, observability, or retrieval-enabled systems.”
How would you debug a deployment that works in staging but fails at the customer's site?
How to answer
Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.
- Compare versions, config and environment variables
- Check network rules, proxies and certificates (common in enterprise)
- Look at resource limits and permissions
- Add the missing check to your install steps afterwards
Tip: List the usual suspects and how you'd check each without full access.
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