AI/LLM Architect

Project Overview We're building an innovative platform that's reimagining how personal coaching works in the digital age. Our solution connects experts with their audience through AI-powered coaching programs that scale personalized guidance. The Challenge We're Solving The challenge we're solving is twofold: users want personalized guidance through structured programs, but coaches have limited time and capacity to assist individuals. Our AI system bridges this gap by automating coaching interactions while maintaining the coach's unique voice and expertise. What Makes Us Unique What makes our platform unique is its dual focus - not only does it provide personalized coaching to users following dynamic programs, but it also equips coaches with powerful AI tools to manage their client relationships at scale. Our AI systems help program creators: Monitor progress across all participants Identify who needs additional attention Provide communication tools for direct interaction when necessary Generate insights about their program's effectiveness This comprehensive approach saves coaches significant time while actually improving the quality of their programs. Technical Foundation Technically, our platform is built on Google's Gemini LLM with structured output capabilities to ensure consistent, high-quality AI interactions. We've developed a robust TypeScript backend running on Cloudflare's serverless infrastructure for optimal scaling and performance. Data is managed through PostgreSQL with Drizzle ORM providing type-safe database operations. This modern stack allows us to create sophisticated AI conversational experiences while maintaining reliability and performance. Our AI systems extend beyond backend logic - they also drive dynamic UI generation, adapting interface elements and user flows in real-time based on coaching context and user needs. This requires architecting AI systems that can generate structured outputs suitable for frontend consumption while maintaining consistency and user experience quality. As our AI/LLM Engineer, you'll be developing the core AI capabilities that make this vision possible - creating conversational systems that can understand user goals, provide personalized guidance through dynamic programs, and help coaches deliver value at scale without sacrificing quality. Key Responsibilities • Design and implement AI systems that deliver personalized coaching through dynamic programs • Build autonomous agent systems that proactively monitor user engagement, detect coaching opportunities, and trigger appropriate interventions without human oversight • Architect AI-driven UI systems where interface elements, user flows, and content presentation are dynamically generated and adapted by AI based on user context and program requirements • Develop AI analytics capabilities that help program creators monitor participant progress and identify coaching opportunities • Create efficient data models and queries that capture coaching relationships, program structures, user progress, and interaction patterns • Build and optimize AI workflows that scale expertise while following structured coaching programs • Design agent orchestration systems that coordinate between conversational interfaces and background analytical agents • Collaborate with frontend teams to define how AI systems generate and control UI components dynamically Implement systems for continuous AI improvement based on user engagement and program effectiveness data • Collaborate across engineering teams to integrate AI functionality with frontend and database components • Optimize AI performance and reliability in our Cloudflare-based environment Skills, Knowledge and Expertise • 4+ years of experience with AI/ML systems, with significant focus on language models • Real experience building agentic systems, not just chatbots - our platform requires both conversational AI interfaces and sophisticated background agents that autonomously monitor progress, analyze patterns, and trigger interventions • Proven experience building production applications with LLMs that go beyond simple Q&A - including multi-step reasoning, goal-oriented behavior, and autonomous decision-making • Experience with major LLM providers (OpenAI, Anthropic, Google, etc.) - with preference for Google Gemini experience given our tech stack • Strong expertise in prompt engineering for both interactive and autonomous agent behaviors Experience with LLM function calling and structured outputs • Experience designing AI systems that generate dynamic UI components and structured data for frontend consumption • Deep understanding of AI context management, retrieval, and memory systems • Proficiency with structured output frameworks for controlling LLM behavior and reasoning patterns • Experience designing and implementing agent orchestration systems that coordinate multiple AI workflows • Experience with SQL databases, including both raw SQL and ORM tools like Drizzle • Knowledge of vector databases for AI applications and similarity search • Strong algorithmic background and problem-solving skills • Ability to stay current with the latest AI research and implement emerging best practices Apply tot his job