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We are the global test and automation specialists, powering next-generation technologies through sophisticated solutions. Behind every electronic device you use, Teradyne's test technology ensures your device works right the first time, every time! Our portfolio of automation solutions help manufacturers to develop and deliver products quickly, efficiently and cost-effectively. Together, Teradyne companies deliver manufacturing automation across industries and applications around the world! We attract, develop, and retain a high-performance workforce, comprised of people with diverse backgrounds and a shared drive for excellence. We strive to foster a positive and inclusive work environment that helps employees, and communities, thrive. 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 QA/Validation Lead Engineer for AI Initiatives is responsible for leading the end-to-end validation, testing, and quality assurance of all AI/ML systems from a data-centric perspective. This role ensures that proper data sources, structures, pipelines, and governance frameworks are validated and maintained across all AI initiatives, including generative AI, agentic systems, and human-in-the-loop workflows. The role combines strategic QA leadership with hands-on technical validation to safeguard the accuracy, reliability, compliance, and ethical use of data powering AI solutions. This position reports to the IT Quality Assurance Manager . Validate that AI/ML models are consuming accurate, authorized, and properly structured data sources. Design and execute data quality test strategies to assess completeness, consistency, lineage, and timeliness of training and inference data. Identify and flag data hallucinations, logic errors, and edge cases in AI model outputs traceable to data issues. Develop and lead comprehensive test strategies for AI/ML systems, including accuracy, bias, robustness, and regression testing. Oversee scenario-based testing and output validation for generative AI and LLM-driven applications. Automate validation suites for agentic/multi-agent systems, integration testing, and CI/CD pipelines for ML models. Assess AI model performance through both manual and automated review, with emphasis on data quality impact on outputs. Validate prompt engineering outputs from a data accuracy standpoint, ensuring responses are grounded in verified data sources. Conduct scenario testing to identify cases where data gaps or structural flaws produce unreliable outputs. Partner with prompt engineers to optimize data retrieval and grounding strategies. Ensure all AI data sources and structures meet governance, regulatory, and compliance standards. Lead audit processes, documentation, and risk assessments related to data usage in AI systems Conduct bias detection and explainability testing to ensure ethical and compliant AI use Maintain traceability of data lineage for regulatory reporting and audit readiness. Validate data flows across human-plus-AI workflows and agent orchestration systems. Ensure seamless data integration across multi-agent architectures and API interfaces. Collaborate with data engineering, data science, AI/ML engineering, and product teams to establish data quality standards. 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. Education and Training Bachelor’s degree in business, information technology or related field (Master's in Computer Science, Data Science, Engineering, or related field preferred). Experience 7+ years in QA/validation engineering; 2+ years focused on AI/ML or data-intensive systems. Preferably a software test automation engineer with hands-on coding experience. He/she should also have a solid understanding of databases to assess structural correctness, along with familiarity with regulatory and compliance standards to support or lead audit-related activities. Technical Skills Programming languages such as Python, Java, or similar; SQL; test automation frameworks; ML metrics; and data profiling tools. Generative AI, agent orchestration, prompt engineering advanced skills. Data lineage, data governance, schema validation, ETL/ELT testing, data lake/warehouse structures. Familiar with AI ethics, risk management, audit processes. Leadership, cross-functional collaboration, change management, technical documentation, stakeholder communication. Key Competencies Analytical Expertise: Advanced skills in data analysis, process optimization, and problem-solving. Communication: Exceptional written, verbal, and visual communication skills, with the ability to engage both technical and non-technical audiences. Collaboration: Proven ability to work effectively with stakeholders across multiple levels and departments, including balancing competing priorities (negotiation skills). Adaptability: Ability to manage ambiguity and shifting priorities in a fast-paced environment. Preferred Qualifications Experience with multi-agent testing and API integration validation. Knowledge of AI-human interaction design and workflow optimization. Certifications in AI/ML, data governance, or quality engineering. Experience establishing QA Centers of Excellence for AI programs. Compensation: The base salary range for this role is $126,100 to 201,800. 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. Please click here to see details.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.