Full-Stack Engineer – AI Systems

About ActAI There 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. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things Role We are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users. Focus Build end-to-end product features across frontend, backend, and AI integrationsDesign agent workflows that handle planning, tool use, failure, and recovery across multiple steps.Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditionsDesign real-time AI interactions with streaming, partial results, and tight latency constraintsImprove system reliability, observability, and fallback mechanismsCollaborate closely with ML, backend, and product teams to ship features end-to-endContinuously iterate based on real usage and failure modes Ideal Experiences Strong experience in full stack engineering (frontend + backend)Solid understanding of system design and API architectureExperience working with LLMs, RAG systems, or AI-powered applicationsAbility to handle ambiguity and make pragmatic engineering decisionsStrong ownership - able to take features from idea to productionComfort working in fast-moving environments with evolving requirements Outcomes Own and ship AI-native product features that move beyond chat into persistent, goal-driven workflowsDesign and deploy agent workflows that reliably complete multi-step tasks across tools and sessionsReduce latency and improve responsiveness of AI interactions while maintaining output qualityBuild robust fallback and recovery mechanisms for LLM and tool failures in production environmentsImprove the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoringEstablish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systemsContribute to a product experience where AI feels proactive, consistent, and dependable over time Tech Stack Next.jsPythonNodeJsPytorchOpenAI / Anthropic / open-source LLMsSQl & noSQLKubernetesDocker How We Work The best products today in the world were built by small, world class teams. We 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. Joining 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 Interview process If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.