Principal AI Engineer (AI games)

UserWise is an innovative game production studio focused on developing and scaling mobile games globally through AI-assisted workflows. Unlike traditional game teams, UserWise emphasizes ownership, clarity, and speed, leveraging AI-driven systems to accelerate the entire game development lifecycle. The team operates globally, building production-ready games and scaling them via LiveOps. The Principal AI Engineer role is a senior individual contributor position responsible for designing and owning the AI infrastructure and automation layer that powers the studio’s game production processes. Reporting to the Head of Internal Games and collaborating closely with the Chief AI Officer and cross-functional teams, this role aims to streamline the journey from concept to launch and scaling by building reliable, production-grade AI systems that teams depend on daily.

Key Responsibilities
- Own the technical architecture for AI and automation across Internal Games, establishing shared infrastructure, engineering standards, and reusable patterns.
- Develop AI agents, tools, and automated workflows spanning opportunity research, prototyping, creative production, QA, launch testing, and LiveOps.
- Design scalable systems that accelerate movement from idea to prototype, prototype to test, and test to launch decisions.
- Integrate external AI/LLM models and APIs (such as Claude Code, MCP servers, Cursor) with Unity pipelines, development environments, and internal tools.
- Build AI-powered analytics and reporting tools that transform game, production, and user acquisition data into actionable insights.
- Create monitoring systems to detect workflow bottlenecks, failures, and data gaps before they impact production timelines.
- Collaborate with Product Builders, Producers, UA, Creative, QA, and Game Operations teams to identify and automate high-impact manual tasks.
- Develop AI-assisted workflows within Unity and other platforms to provide meaningful production leverage.
- Evaluate and adopt new AI models, tools, and approaches that deliver measurable advantages, retiring ineffective ones promptly.
- Enhance 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.
- Serve as the senior technical expert on applied AI, mentoring engineers and enabling both technical and non-technical teams to utilize AI effectively.

Required Qualifications
- Extensive software engineering experience with a proven track record of designing and shipping production systems.
- Recent hands-on experience with large language models (LLMs), AI APIs, agents, or automation platforms.
- Demonstrated success in delivering AI-powered systems, internal tools, or automation workflows actively used in production environments.
- Strong programming and systems engineering fundamentals.
- Familiarity 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.
- Solid understanding of data pipelines, analytics, and leveraging data to drive automated decisions or reporting.
- Ability to design reusable, scalable, and reliable systems rather than one-off prototypes.
- Capability to translate ambiguous challenges across product, design, art, UA, QA, and operations into technical solutions.
- Sound judgment regarding build vs. buy decisions, model selection, performance, reliability, security, and cost considerations.
- Comfortable working in a fast-evolving technical environment with rapidly changing tools and models.
- High ownership mentality, proactively identifying problems and delivering solutions without waiting for perfect information.

Preferred Qualifications and Benefits
- Experience with Unity and C# development.
- Background in building tools or infrastructure specifically for game development.
- Experience in mobile gaming or other fast-iteration consumer products.
- Familiarity with free-to-play (F2P) metrics such as retention, engagement, CPI, monetization, and LTV.

What Success Looks Like
- Teams achieve significantly faster development cycles due to the systems and automation implemented.
- AI workflows evolve into reusable studio-wide capabilities rather than isolated experiments.
- Product teams can rapidly move from ideas to playable tests.
- Increasing automation reduces repetitive production tasks.
- Enhanced visibility into game performance and workflow health.
- AI systems maintain reliability, measurability, and cost efficiency.
- New AI capabilities are evaluated and adopted quickly without disrupting ongoing production.

Work Environment and Benefits
UserWise offers a studio-wide impact role with high ownership and a hands-on approach to both architecture and execution. The environment encourages rapid prototyping, deployment, measurement, and continuous improvement. AI is deeply embedded in the design, build, test, and scale processes, emphasizing practical impact over theoretical research. The studio maintains low bureaucracy, focusing on building effective solutions rather than adding process overhead. Compensation is competitive and includes paid time off, performance bonuses, and annual performance reviews.