Backend Engineer, AI Systems

ppThere are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. /p pOur product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations /p pOur objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things /p h3Role /h3 pAs a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience. Build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. /p h3Focus /h3 ul liBuild and operate backend systems that serve AI-powered features in production. /li liDesign inference pipelines and orchestration layers that handle multi-step workflows, tool calls, and retries /li liManage the full lifecycle of AI requests: routing, caching, batching, streaming, and state management /li liOptimize latency, throughput, and cost across model inference and downstream systems /li liDesign systems that remain reliable despite non-deterministic model behavior and external dependencies /li liImplement observability for AI systems, including logging, tracing, and debugging of model outputs and failures /li liCollaborate with ML and product teams to translate model capabilities into stable, production-grade APIs /li /ul h3Ideal Experiences /h3 ul liExperience running high-throughput, low-latency services. /li liFamiliarity with AI inference patterns (LLMs, embeddings, multimodal). /li liBias toward shipping and learning from production behavior. /li /ul h3Outcomes /h3 ul liBackend systems run reliably at scale, handling production AI traffic with low latency and high throughput. /li liMulti-step AI workflows complete successfully across tools and services, with robust handling of failures and retries /li liAPIs are stable, clear, and support seamless integration with frontend and ML systems. /li liProduction incidents are quickly detected, diagnosed, and resolved, minimizing user impact. /li liIterative improvements based on real usage continuously increase system performance and reliability. /li liSystem design evolves to support increasing scale, complexity, and new AI capabilities without major rewrites. /li liPython /li liNodeJs /li liPytorch /li liOpenAI / Anthropic / open-source LLMs /li liSQl noSQL /li liDocker /li /ul h3How We Work /h3 pThe best products today in the world were built by small, world class teams. /p pWe are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. /p pJoining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product /p /p #J-18808-Ljbffr