Design, build, and maintain full stack applications that integrate generative AI and traditional machine learning capabilities into real world products and workflows
Develop scalable backend services, APIs, and data pipelines that support AI powered systems from prototype through production
Build intuitive, responsive frontend experiences that enable teams and studios to effectively interact with AI driven tools
Rapidly prototype and iterate on new ideas to validate approaches, explore feasibility, and assess impact, then evolve successful concepts into reliable systems
Apply a range of AI and machine learning techniques, including generative models and more traditional approaches, selecting the right tools for each problem
Implement and integrate AI systems using emerging standards such as Model Context Protocol to enable flexible, modular, and interoperable AI driven workflows
Partner cross functionally with research, product, platform, security, and studio engineering teams to translate capabilities into practical, deployable solutions
Own systems end to end, including architecture, implementation, deployment, monitoring, and ongoing improvement
Contribute to shared platforms, tooling, and engineering best practices that accelerate AI adoption across the organization
Help ensure AI systems are reliable, performant, secure, and responsibly deployed in production environments

5+ years of experience in data science or similar role
Strong proficiency in Python and JavaScript or TypeScript, with experience building backend services and frontend applications using modern frameworks
Experience developing and shipping full stack software in production environments, with a focus on reliability, performance, and maintainability
Experience integrating AI and machine learning systems into real world applications and workflows, including model inference, performance tradeoffs, and modern orchestration approaches such as tool calling, retrieval augmented systems, or protocols like Model Context Protocol
Hands-on experience with cloud infrastructure such as Azure, Google Cloud Platform, or similar environments, including deploying and operating services at scale
Working knowledge of machine learning fundamentals and applied AI techniques, including familiarity with deep learning approaches such as convolutional neural networks and generative models
Comfort working with servers, containerization, and modern infrastructure practices such as Docker, Kubernetes, and cloud managed services
Ability to operate in fast moving, ambiguous environments, balancing experimentation with delivery and iteration
Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical partners

Medical, dental, vision, health savings account or health reimbursement account, healthcare spending accounts, dependent care spending accounts, life and AD&D insurance, disability insurance
401(k) with Company match, tuition reimbursement, charitable donation matching
Paid holidays and vacation, paid sick time, floating holidays, compassion and bereavement leaves, parental leave
Mental health & wellbeing programs, fitness programs, free and discounted games, and a variety of other voluntary benefit programs like supplemental life & disability, legal service, ID protection, rental insurance, and others
Relocation assistance if the Company requires that you move geographic locations for the job

Full Stack Engineer, GenAI

Key skills