Senior AI Application Engineer

<div class="content-intro"><p><em>At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5goinqa1 _f8pj13af _9oik18uv _1bnxglyw _jf4cnqa1 _30l313af _1nrm18uv _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" href="http://klaviyo.com/careers" data-renderer-mark="true">klaviyo.com/careers</a>&nbsp;to see how we empower creators to own their own destiny.</em></p></div><p>At Klaviyo, the ARIA (Applications, Resources, Intelligence, and Automations) team is building the AI systems that transform how our employees work. We are looking for a Senior IT App Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools from the ground up. This role sits at the intersection of applied AI research and full-stack software engineering. You will own everything from LLM integration architecture and RAG system design to CI/CD pipeline management and production observability. If you want to build AI that real people use at scale every day, this is the role for you.</p> <p><strong>How you’ll make a difference:</strong></p> <ul> <li><strong>Design and build LLM-powered applications: </strong>Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance.</li> <li><strong>Build and maintain AI integration pipelines: </strong>Design robust, scalable API integrations between AI models and internal systems such as HRIS, ticketing, CRM, and knowledge bases, ensuring reliability, low latency, and high availability.</li> <li><strong>Develop full-stack AI features end-to-end: </strong>Own the complete development of AI features across the stack from backend model orchestration and API layers to frontend interfaces that make AI accessible to non-technical employees.</li> <li><strong>Architect and manage CI/CD pipelines for AI systems: </strong>Build and maintain automated deployment pipelines for AI models and services, including model evaluation frameworks, A/B testing infrastructure, and safe rollout strategies.</li> <li><strong>Implement RAG and retrieval systems: </