Own the design and implementation of WISEcode’s automated quality engineering ecosystem. Build AI-augmented UI, API, integration, regression, database, performance, and reliability testing frameworks for ASP.NET and Blazor applications. Integrate testing into CI/CD, improve observability and release confidence, investigate failures and race conditions, validate AI/ML outputs, and establish scalable quality standards and metrics across engineering teams.
JOIN THE MOVEMENT FOR HEALTH EMPOWERMENT AT WISEcode
WISEcode is on a mission to transform how people understand, choose, and enjoy the foods they eat. We are not building another static health app. We are pioneering an intelligent, interactive experience that empowers families with clarity, confidence, and curiosity around
everyday decisions.
THE OPPORTUNITY
We are hiring a Senior Software Quality Engineer to architect and build the automated QA framework for the WISEintelligence platform.
This is not a traditional manual QA role.
We are looking for an engineering-minded quality leader who thinks systematically about correctness, regression prevention, observability, deterministic behavior, and long-term platform reliability. You will help establish the technical and cultural foundation for how quality engineering operates at WISEcode.
The WISEintelligence platform spans:
• Rich ASP.NET Blazor applications
• Deep domain-driven business logic
• AI-assisted workflows
• Large-scale Postgres-backed system and analytical databases like
DuckDb/Motherduck.
• Complex data transformations and computation pipelines
• Highly dynamic and stateful user experiences
This role requires someone who enjoys understanding sophisticated systems deeply and building durable automation around them.
You will work closely with engineering leadership, product teams, and Principal Engineers to create a scalable automated testing strategy that evolves alongside the platform.
About the role
As Senior Software Quality Engineer, you will own the design and implementation of WISEcode’s automated quality engineering ecosystem.
You will:
• Build and evolve automated testing frameworks for ASP.NET
• Applying 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
This role requires someone who can move fluidly between:
• UI automation
• Backend/API testing
• Database validation
• CI/CD integration
• Performance and reliability thinking
• Test architecture
• Developer tooling
You should be comfortable reasoning across the entire application stack, not just isolated test scripts.
What You'll Work On
- Designing and implementing AI-augmented UI testing frameworks for ASP.NET, using
LLM-assisted test generation to accelerate coverage - Building reliable end-to-end testing infrastructure with Playwright, Selenium, or
equivalent frameworks, enhanced by AI-driven test authoring and self-healing selectors - Developing API and integration test suites for ASP.NET services, leveraging AI tooling to
generate edge cases and flag coverage gaps - Creating reusable testing abstractions and patterns that scale across teams, designed to
be extended by AI copilots as well as engineers - Improving release confidence through regression automation, validation pipelines, and AI-assisted anomaly detection
- Building automated validation around complex nutrition and food intelligence computations, including testing strategies for AI/ML-driven outputs
- Partnering with engineers to improve application testability and observability, using AI
tools to surface blind spots - Integrating automated testing into CI/CD workflows, with AI-assisted triage of failures
and flaky tests - Helping define quality metrics, failure visibility, and release readiness standards,
informed by AI-generated insights from test telemetry - Investigating intermittent failures, race conditions, state management issues, and environment inconsistencies, using AI-assisted root-cause analysis
- Contributing to performance, reliability, and scalability testing strategies, incorporating AI-based load and behavior modeling
- Applying AI-assisted tooling and automation broadly to improve engineering productivity, testing coverage, and speed of iteration
What Success Looks like
- Within the first several months, you are:
- Shipping reliable, AI-augmented automated tests into production CI/CD workflows
- Reducing manual regression testing significantly through AI-assisted test generation and maintenance
- Building confidence in release quality across engineering teams via AI-informed quality signals
- Establishing scalable testing patterns — built with and for AI tooling — that other engineers can extend
- Helping engineers think proactively about quality rather than reactively about bugs, supported by AI-driven early warning systems
- Creating visibility into system health, regressions, and application reliability through AI- powered dashboards and insights
- Operating as a force multiplier across the engineering organization by embedding AI leverage into everyday testing workflows.
Over time, success means helping WISEcode build an engineering culture where quality is engineered into the system itself - not inspected afterward.
AI Skills and Mindset
WISEcode is an AI-native company. Quality engineering is expected to evolve alongside AI-assisted development and intelligent systems.
You will:
• 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
We are not looking for someone who treats AI as novelty. We are looking for someone who treats it as infrastructure.
Required Qualifications
- 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 have
- 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
Why join WISEcode
- Help define the quality foundation for one of the most ambitious food intelligence and AI platforms in the world
- Build systems that directly impact trust, correctness, and platform reliability
- Work closely with senior technical leadership and Principal Engineers
- Operate in an engineering culture that values systems thinking, ownership, and technical depth
- Competitive compensation, benefits, and opportunities for rapid growth and impact
- Solve meaningful technical problems at the intersection of AI, data, computation, and human health
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