• Build velocity across new growth workstreams — you are the person who gets workflows from spec to production • Integration reliability — connections between systems work, handle errors gracefully, and are maintained as tools evolve • Workflow documentation — every workflow you build is documented clearly enough that a domain specialist can understand, tune, and improve it without your involvement • Agent orchestration workflows across growth use cases — automating the decisions and executions that today require human intervention across paid media, lifecycle messaging, organic content, conversion optimization, incentives, and other growth levers • Integrations between our AI reasoning layer, growth execution platforms, data infrastructure, experimentation systems, and analytics tools • Shared agent infrastructure components — reusable workflow patterns, prompt libraries, and integration clients that every growth workstream draws from • Monitoring and audit logging — ensuring every agent action is traceable, versioned, and queryable for governance and continuous improvement • Creative and content generation pipelines — automating the brief-to-variant-to-distribution loop across growth channels.

• You’ll work directly with the AI Growth Infrastructure Lead, the Growth Workflow Specialists across channels, and the domain experts who spec the workflows you build. • You’ll operate within the Growth Foundations Group — the centralized team that builds the engine every product team in the business runs on. • As AI Engineer, Growth, you will be the second builder on this engine. Working alongside our lead architect, you execute — building, shipping, and iterating the agent orchestrations, automated workflows, and system integrations that power every growth work-stream: paid growth, lifecycle, organic search, CRO, incentives, referrals, and beyond.

• Design, develop, test, deploy, and maintain TLI mobile applications using React Native • Implement user-friendly UX/UI designs using a solid understanding of UI/UX principles • Serve as the primary responder for live production incidents affecting lead-generation mobile apps • Build and deploy to App Store and Google Play • Constantly grow expertise in new development trends, specifically AI and automation

• Lead the design and development of our production inference platform. • Define the technical roadmap for inference infrastructure, model serving, and runtime optimization. • Build and operate scalable, cost-effective systems for serving large language models in production. • Evaluate and integrate modern inference technologies, frameworks, and serving runtimes. • Optimize latency, throughput, GPU utilization, memory efficiency, and infrastructure cost. • Develop systems for model deployment, traffic routing, autoscaling, scheduling, observability, and operational excellence. • Partner with ML engineers to productionize new models and inference techniques. • Establish benchmarking methodologies to evaluate new models, runtimes, and hardware. • Make key architectural decisions around when to build internally versus leverage open-source or commercial solutions. • Mentor engineers as the team grows and help establish engineering best practices for AI infrastructure.