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Description & Requirements
Our Quality Verification and Standards (QVS) team is an integral part of our development process, consistently delivering actionable insights that support our game teams to optimize software performance and elevate gameplay. Their dedicated efforts ensure that we deliver cutting-edge entertainment experiences that captivate and inspire players and fans globally.
This Quality Designer I role is focused on ensuring and enhancing game quality for The Sims 4 by leveraging a proactive approach to integrating AI-assisted testing methodologies. The ideal candidate will combine their strong analytical skills with a passion for emerging technologies to execute and design effective test scenarios, critically analyze complex data sets (including those from AI tools), and validate AI-generated findings. With a keen understanding of AI/ML concepts in testing, they will translate insights into actionable QV strategies. This position requires advanced problem-solving for ambiguous issues that AI might miss, a continuous learning mindset for AI and analytics, and the ability to articulate nuanced player-centric feedback. The role involves creatively designing contextual tests that complement AI's capabilities and proactively influencing quality throughout the game development lifecycle by applying advanced testing techniques and data insights.
Technical Skills:
Scripting/Debugging Tools & AI-Assisted Testing Acumen: (Intermediate/Advanced) - Some exposure to or willingness to learn basic scripting or in-game debugging tools. Strong interest in test automation principles and a proactive approach to learning and applying AI-powered testing tools, platforms, or AI-assisted test generation techniques. Understanding how to effectively utilize and interpret outputs from such tools.
Advanced Data Interpretation & AI Output Validation: (Intermediate/Advanced) - Ability to not only read and understand QA metrics but also to critically analyze and interpret complex data sets, including those generated by AI-driven testing or analytics. Capable of validating AI findings, identifying potential biases or anomalies, and translating AI-driven insights into actionable QV strategies.
Understanding of AI/ML Concepts in Testing: (Basic/Intermediate) - Familiarity with fundamental AI/Machine Learning concepts as they apply to software/game testing (e.g., types of AI testing tools, data requirements for AI, limitations of AI in testing, ethical considerations). Ability to understand how AI tools derive their results.
Soft Skills:
Problem-Solving & Complex Analytical Reasoning: (Intermediate/Advanced) - Ability to analyze complex, ambiguous, or novel issues, including those related to emergent game behaviors or subtle player experience degradations that AI might miss. Capable of identifying root causes in intricate systems and proposing creative, context-aware solutions.
Adaptability & Continuous Learning Mindset (especially in AI & Analytics): (Advanced) - Quick to adapt to new processes and passionate about proactively learning and mastering new aspects of game quality, with a specific emphasis on evolving QA methodologies, AI in testing, advanced data analytics, and observability tools.
Qualitative & Player-Centric Feedback Articulation: (Advanced) - Exceptional ability to identify, articulate, and advocate for qualitative aspects of the player experience (e.g., fun factor, intuitive design, emotional impact, narrative coherence) that go beyond simple bug detection and which AI tools may struggle to assess.
Creative & Contextual Test Design: (Intermediate/Advanced) - Skill in designing innovative and contextual test scenarios that explore the boundaries of game systems, player creativity, and potential for unexpected interactions, complementing AI's more systematic approaches. This includes strong exploratory testing skills informed by human intuition.
Experience Levels:
Experience with AI-driven Test Insights (Desirable): (Basic) - Demonstrated experience in working with or interpreting data/insights from AI-enhanced testing tools or analytics platforms is a significant plus.
Domain Knowledge:
The Sims 4 Gameplay, Systems, & Emergent Behavior Acumen: (Intermediate/Advanced) - Strong understanding of core gameplay mechanics, expansion packs, common player experiences, and a keen sense for anticipating, identifying, and testing for complex emergent behaviors and their impact on game stability and player experience within The Sims 4's sandbox environment.
Video Game Development Lifecycle & Proactive Quality Influence: (Intermediate/Advanced) - Familiarity with the stages of game development and the role of QV within it, with an emphasis on proactively identifying opportunities to leverage advanced testing techniques (including AI-assisted methods) and data insights to influence quality earlier in the development cycle.