Manager, Intelligent AI Systems
Razer is hiring a Manager, Intelligent AI Systems in Singapore, Singapore. Level rates it ; you can apply on Razer.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions OpenAI and AI agents among its tools and skills.
- Level classes it as a mid-level role.
- Razer has 148 other open roles on Level.
AI in this role
Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
Job Responsibilities :
This role will focus on leading the development of intelligent autonomous systems for game developers and players. The ideal candidate will have strong expertise in reinforcement learning (RL) and agent-based modeling, along with the ability to apply a broad range of AI techniques to build robust gameplay agents and adaptive in-game behaviors. This role involves working closely with AI engineers, game developers, and software engineers to deliver scalable, production-ready intelligent systems that enhance exploration, automation, and fast iteration across diverse gaming environments.Essential Duties and Responsibilities
- Lead and mentor a team developing intelligent gameplay agents and autonomous systems for in-house AI services.
- Define the technical roadmap for agent-based intelligence, supporting multiple game engines, genres, and gameplay objectives.
- Drive research and development across reinforcement learning, imitation learning, planning, and hybrid approaches as needed.
- Ensure agent solutions are robust, generalizable, and scalable across diverse game mechanics and player behaviors.
- Establish evaluation frameworks and success metrics for autonomy, task success, stability, and real-world performance.
- Collaborate with engineering teams to support deployment, integration, and scaling of intelligent agents into production pipelines.
- Promote best practices in experiment tracking, reproducibility, and large-scale training workflows.
- Communicate technical progress, trade-offs, and long-term strategy effectively to cross-functional stakeholders.
- Stay updated with advancements in intelligent systems, including multi-agent learning, agentic AI, and adaptive decision-making.
Pre-Requisites :
Qualifications
- Proven experience leading or mentoring teams building autonomous agents or applied AI systems.
- Strong proficiency in Python; experience with C++ or Rust is a plus.
- Strong foundation in reinforcement learning methods (policy-based, value-based, actor-critic) and agent training workflows.
- Familiarity with simulation environments and game engines (e.g., OpenAI Gym, Unity, Unreal Engine).
- Experience scaling experimentation, training pipelines, and evaluation processes for agent-based systems.
- Strong analytical, debugging, and problem-solving skills in complex AI systems.
- Excellent communication and collaboration skills across technical and non-technical stakeholders.
Preferred
- Experience with multi-agent systems, self-play, adversarial training, or population-based methods.
- Exposure to imitation learning, offline RL, planning-based agents, or hybrid autonomy approaches.
- Experience integrating agent services via APIs, RabbitMQ, gRPC, or REST-based microservices.
- Familiarity with experiment management, reproducibility tooling, and evaluation automation.
- Background in gaming AI, robotics, simulation, or control systems is a plus.
Education & Experience
- Master’s or PhD in a relevant field (Computer Science, AI, Machine Learning, etc.).
- 3+ years of applied experience in reinforcement learning, agent-based AI, or intelligent autonomous systems, including demonstrated leadership responsibilities (academic or industry).
Travel Requirements
Role based in Singapore office, with occasional travel (up to 1 trip per year) for conferences, research collaborations, or business meetings.
Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.
Are you game?
How we rate this
Manager, Intelligent AI Systems at Razer rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through how you've used OpenAI in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI agents and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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