Senior AI Engineer - Applied

13 Minutes ago • 2 Years +
Research Development

Job Description

This AI Engineer role within the Applied AI Pod focuses on evaluating, integrating, and scaling 3rd-party AI tools into Razer’s internal AI stack. The role involves building robust, scalable systems to bridge external AI solutions with internal infrastructure, enabling intelligent, real-time capabilities across gaming and platform experiences. The ideal candidate is a technically strong generalist with a strong grasp of applied AI/ML, experience with external AI APIs, and skilled in implementing and adapting AI solutions into production-grade systems, collaborating with AI Software Engineers, Data Scientists, and DevOps engineers.
Good To Have:
  • Exposure to vector databases, prompt engineering, or agent-based architectures is a plus.
  • Strong ability to debug, test, and validate AI services in production environments.
  • Ability to clearly communicate technical decisions and trade-offs across engineering and AI teams.
  • Passion for gaming and interest in using AI to enhance user experiences is a plus.
  • Comfortable working in fast-paced, high pressure, agile environment.
Must Have:
  • Build and maintain internal tooling, pipelines, and wrappers to integrate external AI services (LLMs, speech, vision, agents) into Razer's ecosystem.
  • Develop and optimize lightweight in-house AI/ML models to enhance and complement 3rd-party tools.
  • Evaluate and prototype external AI solutions, focusing on code-level integration, architecture compatibility, and system performance.
  • Conduct benchmarking, trade-off analysis, and technical validation for external APIs and platforms.
  • Collaborate with software engineering and DevOps to ensure secure, production-ready, and scalable deployments.
  • Stay up to date with the latest developments in AI SDKs, APIs, toolchains, and deployment strategies.
  • Minimum 2 years of hands-on experience in applied AI/ML, AI systems engineering, or AI integration.
  • Strong proficiency in Python and software engineering fundamentals, including experience with API design, data structures, and modular codebases.
  • Proven experience working with LLM APIs (e.g., OpenAI, Claude, Gemini), AI SDKs, and toolchains such as LangChain, Hugging Face, or RAG frameworks.
  • Experience integrating external AI APIs into internal platforms with attention to latency, throughput, and reliability.
  • Familiarity with cloud environments (AWS, GCP, or Azure) and MLOps workflows (e.g., model deployment, versioning, CI/CD for ML systems).
  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
Perks:
  • Opportunity to make an impact globally.
  • Work across a global team located across 5 continents.
  • Unique, gamer-centric #LifeAtRazer experience.
  • Accelerated growth, both personally and professionally.
  • Certified as a Great Place to Work® in both United States and Singapore.

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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 AI Engineer role sits within the Applied AI Pod, focused on evaluating, integrating, and scaling 3rd-party AI tools into Razer’s internal AI stack. You will play a critical role in building robust, scalable systems that bridge external AI solutions with our internal infrastructure to enable intelligent, real-time capabilities across gaming and platform experiences.

The ideal candidate is a technically strong generalist with a strong grasp of applied AI/ML, experience working with external AI APIs (e.g., GenAI, vision, speech) and skilled in implementing and adapting AI solutions into production-grade systems. You will collaborate closely with AI Software Engineers, Data Scientists, and DevOps engineers to extend Razer’s AI capabilities through reliable, high-performance integration work.

Responsibilities include:

  • Build and maintain internal tooling, pipelines, and wrappers to integrate external AI services (LLMs, speech, vision, agents) into Razer's ecosystem
  • Develop and optimize lightweight in-house AI/ML models to enhance and complement 3rd-party tools
  • Evaluate and prototype external AI solutions, focusing on code-level integration, architecture compatibility, and system performance
  • Conduct benchmarking, trade-off analysis, and technical validation for external APIs and platforms
  • Collaborate with software engineering and DevOps to ensure secure, production-ready, and scalable deployments
  • Stay up to date with the latest developments in AI SDKs, APIs, toolchains, and deployment strategies

Pre-Requisites :

----------------

Pre-Requisites

Technical Skills:

  • Minimum 2 years of hands-on experience in applied AI/ML, AI systems engineering, or AI integration
  • Strong proficiency in Python and software engineering fundamentals, including experience with API design, data structures, and modular codebases
  • Proven experience working with LLM APIs (e.g., OpenAI, Claude, Gemini), AI SDKs, and toolchains such as LangChain, Hugging Face, or RAG frameworks
  • Experience integrating external AI APIs into internal platforms with attention to latency, throughput, and reliability
  • Familiarity with cloud environments (AWS, GCP, or Azure) and MLOps workflows (e.g., model deployment, versioning, CI/CD for ML systems)

Preferred Qualifications

  • Exposure to vector databases, prompt engineering, or agent-based architectures is a plus
  • Strong ability to debug, test, and validate AI services in production environments
  • Ability to clearly communicate technical decisions and trade-offs across engineering and AI teams
  • Passion for gaming and interest in using AI to enhance user experiences is a plus
  • Comfortable working in fast-paced, high pressure, agile environment.

Education & Experience

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline

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