Principal AI Engineer (AI games)

About UserWise We’re building a high-speed, AI-assisted game production team focused on developing and scaling mobile games globally. This is not a traditional game team. We operate with ownership, clarity, and execution speed, using AI-driven workflows to move faster than most studios. We work across a global team, building production-ready games and scaling them through LiveOps. The Role We’re looking for a Principal AI Engineer to build and technically own the AI infrastructure and automation layer powering how our studio finds, builds, tests, launches, and scales games. This is a studio-wide, senior individual contributor role. You’ll report to the Head of Internal Games and work closely with our Chief AI Officer and teams across product, production, engineering, UA, creative, QA, and game operations. Your job is to make the whole system faster: from idea to prototype, prototype to launch test, and test data to a scale, iterate, or kill decision. You won’t just experiment with AI. You’ll build production systems that teams rely on every day. What You’ll Do Own the technical architecture for AI and automation across Internal Games, establishing shared infrastructure, patterns, and engineering standards Build AI agents, tools, and automated workflows across the game production lifecycle, from opportunity research and prototyping through creative production, QA, launch testing, and LiveOps Design reusable systems that enable teams to move from idea → prototype → test → launch significantly faster Integrate external AI/LLM models and APIs (e.g., Claude Code, MCP servers, Cursor) with our development environment, Unity pipelines, and internal tools. Build AI-powered analysis and reporting tools that turn game, production, and UA data into actionable insights Create systems for monitoring workflow health, identifying bottlenecks, failures, and data gaps before they slow production Partner with Product Builders, Producers, UA, Creative, QA, and Game Operations to identify high-impact manual work and automate it Develop AI-assisted workflows within Unity and other development environments where they create meaningful production leverage Rapidly evaluate new models, tools, and approaches, adopting what creates measurable advantage and retiring what doesn’t Improve the reliability, observability, scalability, and cost efficiency of AI systems as usage grows Establish practical guardrails around data access, security, quality, evaluation, and human review Act as the senior technical voice for applied AI within the studio, mentoring engineers and enabling technical and non-technical teams to use AI effectively Requirements What You Bring Significant software engineering experience, with a track record of designing and shipping production systems Recent hands-on experience building with LLMs, AI APIs, agents, or automation platforms Proven experience shipping AI-powered systems, internal tools, or automation workflows that real teams use in production Strong programming and systems engineering fundamentals Experience with modern LLM development patterns including tool/function calling, agentic workflows, model integration, evaluation, and orchestration Experience integrating APIs, third-party platforms, and cloud-based systems Strong understanding of data pipelines, analytics, and using data to power automated decisions or reporting Ability to design reusable systems for reliability and scale rather than one-off prototypes Ability to translate ambiguous problems across product, design, art, UA, QA, and operations into technical solutions Strong judgment around build vs. buy, model selection, performance, reliability, security, and cost Comfort working in a rapidly changing technical environment where tools and models evolve quickly High ownership. You identify problems, make decisions, build, and ship without waiting for perfect information Strong Plus Experience with Unity and C# Experience building tools or infrastructure for game development Mobile gaming or other fast-iteration consumer product experience Familiarity with F2P metrics including retention, engagement, CPI, monetization, and LTV What Success Looks Like Teams move materially faster because of the systems and automation you build AI workflows become reusable studio capabilities rather than isolated individual experiments Product Builders can move from ideas to playable tests faster Repetitive production work is increasingly automated Teams have better visibility into game performance and workflow health AI systems are reliable, measurable, and cost-efficient New AI capabilities can be evaluated and adopted quickly without disrupting production Benefits Environment Studio-wide impact: Build systems that improve how multiple teams operate High ownership: Identify problems and take them through to working solutions Hands-on: Architecture and execution go together High speed: Prototype, deploy, measure, and improve quickly AI-native: AI is embedded in how we design, build, test, and scale games Production-first: Practical impact over theoretical research Low bureaucracy: Build solutions instead of adding process What We Offer Competitive compensation Paid Time Off Performance Bonus Annual Performance Reviews