Playlab

Platform Engineer

• Architect new agent runtime infrastructure that will support us scaling to the next 100x users
• Implement the foundations of multi-person apps and realtime collaboration features
• Design systems that support lab schools redesigning education from the ground up - from AI-native curricula to entirely new operational models
• Collaborate with the ML team to select and build data infrastructure that can power realtime steering of LLM interactions
• Work with product and app engineering to create secure, ephemeral backend sandboxes that enable power users to add sophisticated custom functionality to the apps they’re creating on Playlab
• Contribute to open sourcing components of our platform and supporting country-specific and self-hosted deployments
• Research, make tradeoffs, design and implement the core systems that enable us to rapidly iterate on AI-native educational experiences
• Help design the engineering culture and technical strategy
• Stay on top of new technologies, platforms and techniques to unlock new functionality and improve existing features
• Work cross functionally and with customers so your system designs support the real needs of users as well as engineering goals
• Balance experimentation with production excellence - be quick and creative when exploring new possibilities, ensure reliability, observability, and maintainability when productionizing systems
• Take security and privacy seriously and work it into your architectural decisions
• Work with product and engineering to both set and support the roadmap
• Mentor engineers on system design and platform engineering through pairing and reviews.

Principal Platform Engineer

Product Manager

• Drive Product Execution
• Own the product roadmap: prioritize ruthlessly, write clear specs, and work with design, engineering, and learning teams to ship
• De-risk builds by breaking work into meaningful increments that let us learn as we go
• Make tradeoffs when scope, timeline, and resources collide and communicate those tradeoffs clearly
• Go Deep on the Details
• Write detailed requirements that align design, engineering, and go-to-market teams
• Understand the technical constraints and possibilities, and work side-by-side with engineering
• Engage directly with users, and gather user feedback, usage data, and partner insights to inform decisions
• Build Product Process
• Establish rituals, artifacts, and communication patterns that help a growing team stay aligned
• Create clarity about how product decisions get made, without slowing the team down
• Document what's working so others can build on it
• Collaborate Across Teams
• Work with Learning and Partnerships to translate field feedback into clear priorities and simpler designs
• Coordinate with design to ensure what we build is usable, not just functional
• Refine Strategy as You Learn
• Pressure-test strategic assumptions against what you see in the product and hear from users
• Surface when priorities should shift, and make the case with evidence
• Help leadership make better decisions by bringing clarity to ambiguous situations

Senior Product Manager

Full-stack Engineer

• Architect and ship subsystems across the full stack - from React/Remix frontend to Node.js backend to integrations with Python AI services
• Move fast to learn what works - ship small experiments quickly, then invest in productionizing what proves valuable
• Stay on top of web technologies and best practices - evaluate new tools and patterns that improve the product
• Work cross-functionally with designers, ML engineers, product, and customers to build experiences that solve real user needs
• Write comprehensive tests and documentation for the features you build
• Improve team processes and help drive strategic technical decisions
• Mentor engineers on fullstack development, design patterns, and app architecture through pairing and reviews

Staff Fullstack Engineer

Affiliate Manager

• Design a 24-month, high-rigor cohort for AI-enabled learning environments
• Co-create cohort structure, norms, and learning arc with partners
• Define clear outcomes, milestones, and evidence routines
• Serve as the primary point of contact for key ecosystem partners
• Align sessions, workstreams, and artifacts for a coherent program experience
• Convene and manage multi-organization working groups
• Coach and support heads of school and leaders to articulate ambitious visions
• Translate visions into concrete pilots, staffing plans, and instructional models
• Ensure work ties to academic goals, equity commitments, and community priorities
• Design and facilitate high-quality convenings—virtual and in-person
• Help leaders identify high-leverage AI use cases and coordinate co-build cycles
• Guide learning communities in developing reusable artifacts and curate stories of student agency

Learning Partner

• Ship features across the full stack - from React/Remix frontend to Node.js backend
• Move fast to learn what works - ship experiments quickly and iterate based on feedback
• Be curious - learn and apply web technologies and best practices as you build
• Work collaboratively with designers, other engineers, and product to build features users need
• Write tests and documentation for your code
• Participate actively in code reviews and learn from the team

Fullstack Engineer

Backend Engineer

• Design, build, and maintain production Python services that power AI features with reliability and performance
• Stay on top of emerging frameworks and Python ecosystem - evaluate new tools that improve our capabilities
• Work cross-functionally with ML engineers, platform engineers, and product to ensure services meet real needs
• Balance experimentation with production excellence - prototype quickly with new techniques while ensuring production reliability
• Write comprehensive tests and documentation that make systems understandable and maintainable
• Mentor engineers on Python best practices, service design, and LLM integration patterns

Staff Backend Engineer, Python

Machine Learning Engineer

• Design and build evaluation systems that assess educational AI quality across thousands of conversations - from learning outcomes to bias detection to curriculum alignment
• Build ML systems that enable self-improving app creation - learning from high-quality apps on the platform to automatically scaffold new applications for educators
• Design and prototype downloadable, on-device AI models that work without internet connectivity - critical for privacy and global accessibility
• Develop systems that enable dynamic, fluid interfaces adapting to learning moments - transitioning seamlessly from chat to writing editor to interactive physics simulation as needed
• Build content moderation and safety systems designed specifically for educational discourse
• Implement agentic AI systems that enable educators to create goal-directed applications (e.g., "help students through this project over 2 weeks")
• Build sophisticated RAG systems that integrate diverse educational content with semantic search and knowledge graphs

Staff Machine Learning Engineer

• Ship end-to-end features across the full stack - from React/Remix frontend to Node.js backend to integrations with Python AI services
• Move fast to learn what works - ship small experiments quickly, then invest in productionizing what proves valuable
• Stay on top of web technologies and best practices - evaluate new tools and patterns that improve the product
• Work cross-functionally with designers, ML engineers, product, and customers to build experiences that solve real user needs
• Write comprehensive tests and documentation for the features you build
• Collaborate strongly with peers through code reviews and pairing

Senior Fullstack Engineer

Artificial Intelligence

• Engage in rapid prototyping and planning specific to contexts in a cohort of up to 20 leadership teams.
• Participate in monthly strategy calls and quarterly in-person intensives.
• Interrogate fundamental beliefs about education's structure.
• Leverage Playlab's platform to create custom AI tools that enhance human connectivity within education.

AI Lab School Cohort Application

Infrastructure Engineer

• Build data pipelines that scrub PII, create research datasets, and power the research portal for educational AI studies
• Architect the path toward self-hosted and on-device model deployments for privacy and global accessibility
• Design and implement model orchestration systems that intelligently route requests across multiple AI providers (OpenAI, Anthropic, AWS Bedrock, open-source models)
• Build cost optimization infrastructure - implement conversation compression, prompt caching, and smart model selection to keep AI accessible
• Create comprehensive observability systems for ML operations - track costs, latency, quality, and usage patterns across thousands of applications
• Design and implement infrastructure for fine-tuning and deploying custom models
• Build monitoring and alerting systems that help us maintain reliability as AI interactions scale

Staff ML Infrastructure Engineer

• Design a domain model that enables both institutions (districts, schools, ministries) and individuals (teachers, coaches) to use Playlab successfully
• Clarify how users, organizations, apps, and permissions relate to each other as Playlab scales
• Ensure the model supports Playlab's current partnerships while creating flexibility for future growth
• Specify the controls that give institutions visibility and confidence: user management, app distribution, usage reporting, and appropriate content governance
• Balance institutional needs with Playlab's commitment to educator agency—administrators need oversight without locking down what makes Playlab powerful
• Work with the partnerships team to prioritize based on what's actually blocking deployments
• Define requirements for getting roster data into and out of Playlab at scale—supporting districts and organizations with varied SIS configurations
• Specify integration patterns that work across the fragmented K-12 data landscape (Clever, ClassLink, OneRoster, custom exports)
• Design flows that reduce manual work for IT administrators and partnership teams