Wand AI

Test Job- Head of Software Engineering

Zdalnie, Europe Zdalnie Opublikowano Maj 7, 2026
LokalizacjaZdalnie, Europe
Tryb pracyZdalnie
Opublikowano7 maja 2026
Ostatnio sprawdzono7 maja 2026

Position Summary

We are seeking a Staff AI Software Developer in Test (Staff AI SDET) to help lead the next generation of quality engineering by integrating AI-driven testing approaches and evaluation frameworks into our development process.

This Staff AI SDET will focus on building QA ecosystems, including building QA systems, evaluating, benchmarking, and improving AI-driven testing agents across our engineering streams. The successful candidate will work hands-on to design evaluation strategies, build proof-of-concepts, and conduct experiments to determine how AI can most effectively improve software quality, testing coverage, and engineering efficiency.

The role requires a combination testing expertise, hands-on experimentation with AI agents, and the ability to design a structured QA ecosystem and evaluation processes. Working closely with the QA Lead and engineering teams, this person will identify gaps in current testing approaches and design AI-assisted solutions to address them.

Responsibilities

  • Design and implement QA foundations and evaluation frameworks for assessing AI agents, their workflows and processes.

  • Design and run experiments to assess AI-driven QA processes, including prompt strategies, automation workflows, and agent performance.

  • Benchmark systems across multiple engineering streams to determine accuracy, reliability, cost, and consistency of outputs.

  • Develop approaches for creating synthetic datasets and structured test data to support reliable evaluation.

  • Identify gaps in existing testing approaches and design AI-based solutions or agents to address them.

  • Build proof-of-concepts (POCs) to explore new testing approaches and validate ideas.

  • Structure and document product knowledge, including user journeys, APIs, and business rules, to support AI-assisted testing systems.

  • Evaluate the cost, ROI, and effectiveness of different QA approaches and automation strategies.

  • Collaborate closely with the QA Lead and engineering teams to integrate AI-assisted QA into development workflows.

  • Ensure AI-driven testing processes produce consistent, reliable, and high-quality results.

  • Remain hands-on in building tooling, experiments, and testing infrastructure.

Key Role Requirements

  • Strong background in SDET, test automation.

  • Experience building and maintaining automated testing frameworks and QA tooling.

  • Hands-on experience building proof-of-concepts or experimental systems.

  • Experience evaluating or working with AI systems, LLMs, or agent-based workflows.

  • Ability to design structured experiments and evaluation methodologies.

  • Strong understanding of testing fundamentals, including UI and API automation tools such as Cypress, Playwright, or similar.

  • Experience analysing systems and identifying opportunities to improve processes through automation or AI.

  • Ability to work hands-on while also contributing to process design and strategic improvements.

Preferred Experience

  • Experience working in AI-focused companies or startups.

  • Hands-on experience building or experimenting with AI agents or AI-driven automation workflows in Quality Assurance.

  • Experience designing evaluation frameworks for AI systems.

  • Experience working with synthetic data generation or test data modelling.

  • Familiarity with knowledge graph systems or structured product knowledge mapping.

  • Experience evaluating cost efficiency and ROI of engineering or QA initiatives.

  • Experience working in fast-moving startup environments.

Personal Characteristics

  • Builder mindset with a strong desire to experiment and create new solutions.

  • Proactive and hands-on, comfortable turning ideas into working prototypes.

  • Strong analytical thinking and problem-solving skills.

  • Comfortable working in rapidly evolving technical environments.

  • Curious about emerging AI technologies and their practical applications.

  • Able to think creatively about testing strategies and data generation.

  • Collaborative and comfortable working across engineering and QA teams.

  • Maintains a can-do attitude and flexible approach to tools and technologies.

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