AI Software Test Engineer (SDET)

Aquent; Ann Arbor (MI); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Subsidized health plan

Vision plan

Dental plan

401(k) retirement plan with match

Job summary

Aquent Talent is seeking an experienced QA Automation Engineer to lead testing for AI-powered applications, ML systems, AI agents, and generative AI solutions in a financial technology context. You will build scalable test strategies, validate AI outputs for accuracy and safety, and integrate testing into CI/CD pipelines.

You will collaborate with software and AI engineers, product owners, and security teams to ensure reliability, performance, and governance across complex AI workloads, APIs,

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• 3–6 years of experience in software testing, QA automation, or quality engineering.
• Proven experience developing automated test solutions using Python, Java, JavaScript/TypeScript, or C#.
• Demonstrated experience with API testing and automation tools.
• Strong understanding of test automation principles, the SDLC, Agile methodologies, and CI/CD pipelines.
• Experience testing distributed systems, web applications, and APIs.
• Proficiency in AI Testing concepts including Prompt Testing, Response Evaluation, Hallucination Detection, Agent Workflow Validation, RAG Validation, AI Safety Testing, AI Regression Testing, and AI Benchmarking.
• Expertise in Quality Engineering practices such as Test Automation, API Testing, Integration Testing, Performance Testing, Load Testing, Security Testing, Defect Analysis, and Root Cause Investigation.
• Familiarity with Selenium, Playwright, Postman, JUnit/PyTest, GitHub Actions, Jenkins, Docker, and Kubernetes.

Responsibilities

• Develop and implement comprehensive testing strategies for AI applications, platforms, and services.
• Validate AI model outputs for accuracy, consistency, reliability, and safety, performing adversarial, negative, and edge‑case testing to identify potential failures and hallucinations.
• Design and execute functional, integration, end‑to‑end, regression, and performance tests specifically tailored for AI solutions.
• Create intricate test cases for prompt‑driven, agentic, and retrieval‑based AI workflows, ensuring robust validation of AI guardrails, business rules, permissions, and governance controls.
• Build and maintain advanced automated test frameworks and evaluation pipelines for AI responses and workflows, integrating AI testing seamlessly into CI/CD pipelines.
• Implement automated quality scoring and regression detection mechanisms, and create reusable test data, mocks, simulators, and validation frameworks.
• Test AI agents, workflows, APIs, complex system integrations, and tool‑calling capabilities, validating integrations with external systems, data sources, and enterprise services.
• Verify performance, reliability, scalability, and resiliency of AI workloads, including executing load and stress testing for AI services.
• Collaborate proactively with software engineers, AI engineers, product owners, architects, and security teams, providing critical quality feedback during design reviews and development.
• Contribute significantly to test strategy, quality standards, and best practices, and support production readiness reviews and defect triage activities.
• Contribute to projects such as testing AI chat assistants and copilots, validating AI agent workflows, evaluating retrieval augmented generation (RAG) search quality, automating AI response evaluation frameworks, and performance testing AI services and orchestration platforms.

Skills

Python

Java

JavaScript/TypeScript

C#

API testing

CI/CD

Selenium

Playwright

Postman

JUnit/PyTest

GitHub Actions

Jenkins

Docker

Kubernetes

Test automation

Education

Bachelor's degree in Computer Science or related field

Tools

Selenium

Playwright

Postman

JUnit/PyTest

GitHub Actions

Jenkins

Docker

Kubernetes

Job description

Partnering with Aquent, we are seeking talent for a leading organization at the forefront of financial innovation. This institution is dedicated to building secure, reliable, and cutting‑edge solutions that empower millions of users to achieve their financial goals. Join a team that is shaping the future of technology within the financial industry, driving impact through advanced engineering and a commitment to excellence.

Are you ready to dive into the exciting world of Artificial Intelligence and make a tangible impact on the next generation of intelligent systems? We are looking for a visionary and hands‑on engineer to spearhead the quality assurance of our groundbreaking AI‑powered applications, machine learning systems, AI agents, and generative AI solutions. In this pivotal role, you will be instrumental in ensuring that our AI systems are not just innovative, but also reliable, safe, accurate, and performant, directly contributing to the trust and success of our advanced technology initiatives.

Your Impact & Key Responsibilities

• Develop and implement comprehensive testing strategies for AI applications, platforms, and services.
• Validate AI model outputs for accuracy, consistency, reliability, and safety, performing adversarial, negative, and edge‑case testing to identify potential failures and hallucinations.
• Design and execute functional, integration, end‑to‑end, regression, and performance tests specifically tailored for AI solutions.
• Create intricate test cases for prompt‑driven, agentic, and retrieval‑based AI workflows, ensuring robust validation of AI guardrails, business rules, permissions, and governance controls.
• Build and maintain advanced automated test frameworks and evaluation pipelines for AI responses and workflows, integrating AI testing seamlessly into continuous integration/continuous delivery (CI/CD) pipelines.
• Implement automated quality scoring and regression detection mechanisms, and create reusable test data, mocks, simulators, and validation frameworks.
• Test AI agents, workflows, APIs, complex system integrations, and tool‑calling capabilities, validating integrations with external systems, data sources, and enterprise services.
• Verify performance, reliability, scalability, and resiliency of AI workloads, including executing load and stress testing for AI services.
• Collaborate proactively with software engineers, AI engineers, product owners, architects, and security teams, providing critical quality feedback during design reviews and development.
• Contribute significantly to test strategy, quality standards, and best practices, and support production readiness reviews and defect triage activities.
• Contribute to projects such as testing AI chat assistants and copilots, validating AI agent workflows, evaluating retrieval augmented generation (RAG) search quality, automating AI response evaluation frameworks, and performance testing AI services and orchestration platforms.

Must‑Have Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• 3–6 years of experience in software testing, QA automation, or quality engineering.
• Proven experience developing automated test solutions using Python, Java, JavaScript/TypeScript, or C#.
• Demonstrated experience with API testing and automation tools.
• Strong understanding of test automation principles, the Software Development Life Cycle (SDLC), Agile methodologies, and CI/CD pipelines.
• Experience testing distributed systems, web applications, and APIs.
• Proficiency in AI Testing concepts including Prompt Testing, Response Evaluation, Hallucination Detection, Agent Workflow Validation, RAG Validation, AI Safety Testing, AI Regression Testing, and AI Benchmarking.
• Expertise in Quality Engineering practices such as Test Automation, API Testing, Integration Testing, Performance Testing, Load Testing, Security Testing, Defect Analysis, and Root Cause Investigation.
• Familiarity with industry‑standard tools and technologies like Selenium, Playwright, Postman, JUnit/PyTest, GitHub Actions, Jenkins, Docker, and Kubernetes.

Nice‑to‑Have Qualifications

• 1–3 years of exposure to AI/ML or Generative AI technologies.
• Experience testing Generative AI applications, large language model (LLM)‑based systems, AI agents, RAG applications, or complex platform integrations.
• Familiarity with leading AI models and platforms.
• Experience building evaluation and benchmarking frameworks for AI solutions.
• Experience testing cloud‑native applications on major cloud platforms.
• Knowledge of responsible AI, AI governance, and AI risk management practices, understanding how AI initiatives align with enterprise governance, risk, privacy, and compliance requirements.

Please note: This position is available on a W‑2 employment basis only and is not open to Corp‑to‑Corp (C2C) arrangements. The client is also unable to provide employment‑based visa sponsorship or transfers for this role.

About Aquent Talent

Aquent Talent connects the best talent in marketing, creative, and design with the world’s biggest brands. Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match.

Aquent is an equal‑opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment‑one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.