Senior Software Quality Engineer – AI Automation Tester

WISEcode

12d

About The Position

WISEcode is seeking a Senior Software Quality Engineer to architect and build the automated QA framework for the WISEintelligence platform. This role is for an engineering-minded quality leader focused on correctness, regression prevention, observability, deterministic behavior, and long-term platform reliability. The WISEintelligence platform includes ASP.NET Blazor applications, domain-driven business logic, AI-assisted workflows, large-scale Postgres and analytical databases, complex data transformations, and dynamic user experiences. The successful candidate will work closely with engineering leadership, product teams, and Principal Engineers to create a scalable automated testing strategy. This role requires a deep understanding of sophisticated systems and the ability to build durable automation around them.

Requirements

5–10+ years of professional software engineering or software quality engineering experience
Experience building automated UI testing frameworks
Experience with Playwright, Selenium, Cypress, or equivalent automation tooling
Experience testing APIs and distributed application workflows
Strong understanding of CI/CD pipelines and automated deployment validation
Experience working with relational databases, ideally Postgres
Ability to reason across UI, API, database, and infrastructure boundaries
Strong debugging and systems-thinking skills
Ability to work independently in ambiguous, fast-moving startup environments
Strong engineering judgment and attention to detail

Nice To Haves

Experience with Blazor-specific testing approaches and tooling
Strong coding ability in C#
Experience with performance or load testing
Experience validating AI-assisted or ML-integrated workflows
Experience with observability tooling and production diagnostics
Familiarity with containerized environments and cloud infrastructure
Experience building internal developer tooling or quality platforms
Experience with large-scale enterprise applications or data-intensive systems
Exposure to modern AI-assisted engineering workflows
Strong hands-on experience testing ASP.NET applications
Experience testing ASP.NET Blazor applications or other highly stateful SPA frameworks

Responsibilities

Build and evolve automated testing frameworks for ASP.NET
Apply AI-assisted tooling and automation to improve engineering productivity and testing coverage
Develop reliable end-to-end UI automation for highly interactive workflows
Create API, integration, and regression testing infrastructure
Improve confidence in releases through intelligent automation and observability
Partner closely with engineers to ensure testability is designed into systems early
Help establish quality standards, patterns, and engineering discipline across teams
Design and implement AI-augmented UI testing frameworks for ASP.NET, using LLM-assisted test generation
Build reliable end-to-end testing infrastructure with Playwright, Selenium, or equivalent frameworks, enhanced by AI-driven test authoring and self-healing selectors
Develop API and integration test suites for ASP.NET services, leveraging AI tooling to generate edge cases and flag coverage gaps
Create reusable testing abstractions and patterns that scale across teams, designed to be extended by AI copilots as well as engineers
Improve release confidence through regression automation, validation pipelines, and AI-assisted anomaly detection
Build automated validation around complex nutrition and food intelligence computations, including testing strategies for AI/ML-driven outputs
Partner with engineers to improve application testability and observability, using AI tools to surface blind spots
Integrate automated testing into CI/CD workflows, with AI-assisted triage of failures and flaky tests
Define quality metrics, failure visibility, and release readiness standards, informed by AI-generated insights from test telemetry
Investigate intermittent failures, race conditions, state management issues, and environment inconsistencies, using AI-assisted root-cause analysis
Contribute to performance, reliability, and scalability testing strategies, incorporating AI-based load and behavior modeling
Apply AI-assisted tooling and automation broadly to improve engineering productivity, testing coverage, and speed of iteration
Use AI-assisted development tools to accelerate testing and automation
Help evaluate reliability and failure modes in AI-assisted workflows
Build validation strategies around probabilistic and deterministic systems
Think critically about explainability, reproducibility, and trust in AI-integrated features
Leverage AI to improve test generation, coverage analysis, and debugging workflows