SDET with AI

Synechron•Menlo Park, CA

1d•$110,000 - $115,000

About The Position

Synechron is seeking a Software Development Engineer in Test (SDET) – AI to design, develop, and maintain reliable automated testing solutions for software products and AI-powered applications. The position combines software engineering, quality assurance, test automation, and artificial intelligence to improve product quality, testing efficiency, and release confidence. The SDET will work with developers, product managers, data scientists, DevOps engineers, and other stakeholders, taking technical ownership and helping lead QA initiatives across the software development lifecycle. The role involves leading QA activities, building and maintaining scalable test automation frameworks, integrating automated tests into CI/CD pipelines, testing APIs and databases, and managing test data. It also includes evaluating AI-powered applications for accuracy, consistency, bias, robustness, security, performance, and other quality characteristics. The successful candidate will contribute to test planning and release readiness, analyze results and report defects, mentor QA professionals, and promote continuous improvement. The position is listed with a base salary of $110,000–$115,000 per year if filled in Menlo Park, California; salary varies based on geography and other factors. Synechron describes a multinational workplace with opportunities to work abroad, training and development, coaching, and a diverse global culture.

Requirements

Degree in Computer Science, Engineering, Information Technology, or a related discipline.
Strong programming skills in Python, Java, JavaScript, TypeScript, C#, or a similar language.
Strong understanding of software testing principles, Agile methodologies, version control, and defect life cycle management.
Practical knowledge of automation framework design and maintainable test architecture.
Proficiency with API testing tools such as Postman, REST Assured, Requests, Karate, or equivalent technologies.
Strong SQL knowledge and the ability to validate data across relational or non-relational databases.
Ability to create clear test scenarios, test cases, test scripts, and test reports.
Strong communication, problem-solving, troubleshooting, and collaboration skills.
Ability to apply AI tools to QA activities and develop AI-assisted testing or quality engineering solutions.
Knowledge of AI testing and validation, including prompt and response testing, hallucination detection, accuracy and consistency checks, bias and fairness assessment, robustness testing, data quality validation, model drift monitoring, explainability, security, and performance evaluation.

Nice To Haves

Familiarity with large language models, prompt engineering, retrieval-augmented generation, AI evaluation frameworks, and machine learning workflows.
Knowledge of Selenium, Playwright, Cypress, Appium, Robot Framework, or similar automation tools.
Familiarity with PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Docker, Kubernetes, AWS, Azure, or Google Cloud.
Experience with OpenAI APIs, Azure OpenAI, Hugging Face, LangChain, MLflow, or comparable AI technologies.
Knowledge of Jira, TestRail, Zephyr, Azure Test Plans, or other test management platforms.
Familiarity with chatbot, generative AI, recommendation, forecasting, or other intelligent applications.
Understanding of responsible AI, privacy, compliance, observability, data lineage, and model monitoring principles.

Responsibilities

Lead QA team activities, including test planning, execution, defect management, release validation, and quality reporting.
Design, develop, and maintain scalable automation frameworks for UI, API, integration, regression, and end-to-end testing.
Define automation standards, reusable components, coding guidelines, test metrics, and quality gates.
Integrate automated tests into CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
Develop and execute API automation for RESTful and SOAP services.
Perform database testing and SQL validation, backend verification, data integrity checks, and query-based testing.
Plan and maintain test data management strategies for functional, integration, regression, and AI testing.
Analyze test results, investigate failures, identify quality risks, and report defects with clear technical details.
Participate in requirements reviews, design discussions, sprint planning, and release readiness activities.
Mentor QA professionals and encourage collaboration, ownership, and continuous improvement.
Support functional, performance, security, scalability, usability, and reliability testing.
Apply AI tools to test planning, test case generation, defect analysis, test data creation, and automation maintenance.
Develop AI-assisted testing utilities, automation enhancements, or quality engineering solutions.
Test and validate AI systems, including prompt and response behavior, hallucinations, accuracy, consistency, bias, fairness, robustness, data quality, model drift, explainability, security, and performance.

Benefits

Competitive compensation and benefits package.
Possibility to work abroad.
10 days of paid annual leave, plus sick leave and national holidays.
Maternity and paternity leave plans.
Medical, dental, vision, life, and long- and short-term disability insurance; plans vary by region.
Retirement savings plans.
Higher education certification policy.
Commuter benefits; availability varies by region.
Extensive training opportunities focused on skills, substantive knowledge, and personal development.
On-demand Udemy for Business access to more than 5,000 curated courses.
Coaching opportunities with colleagues from Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
Flexible workplace arrangements, mentoring, internal mobility, learning and development programs.
Opportunity to work on projects for leading banks, financial institutions, and insurance firms.
Diverse, global work culture.