Product Engineer, Applied AI

Product Engineer, Applied AI Pocus exists to supercharge GTM teams. We make every rep a 10x seller. With Pocus, organizations can have fewer, better reps to drive increased pipeline and revenue. How? We’ve created the world’s most powerful, AI-native prospecting platform. Pocus influences nearly half a billion in pipeline per quarter for our customers. We’re trusted by high growth companies like Asana, Monday, Canva, and Miro where Pocus powers up to 50% of their pipeline and eliminates 10+ hrs of work per rep per week. Pocus has hundreds of always-on AI agents doing the manual, tedious work of researching & prospecting so that reps can do what they do best: sell. With Pocus AI agents working for them, rep’s days are simplified. Reps get alerts when compelling events happen, account plans are generated by AI, and agents recommend who to reach out to with the next best action. We’re fortunate to be backed by First Round, Coatue, and execs like CEO Zoom, CPO Adobe, CRO OpenAI, who are helping us usher in this future of sales. The Pocus team is full of humble overachievers that like to move quickly (we call it shiperate), own our work, give customers superpowers, and create magic for our team… all while having a ton of fun. Join us on this next phase of growth! ABOUT THE ROLE Pocus is powered by a custom-built agentic AI platform designed to help users ingest, reason over, and take action on structured and semi-structured data—whether it’s public or private. As an Applied AI Engineer, you’ll work at the intersection of cutting-edge AI and robust systems, helping to design and build intelligent agents that deeply understand data and drive workflows end-to-end. WHAT YOU’LL DO As an Applied AI Engineer at Pocus, you’ll help scale the AI infrastructure that powers our entire product experience. Our stack is built on AWS, with services written in TypeScript and connected through GraphQL. We leverage tools like Clickhouse, Presto, Temporal, and large language models (LLMs) as core building blocks—and default to managed services wherever possible to keep velocity high. In this role, you will - Build agentic AI systems end-to-end: Architect and implement intelligent agents that extract insights from fragmented data sources and power real-world workflows. - Engineer an extensible AI platform: This includes: - A flexible data ingestion layer that connects to warehouses, databases, CRMs, public datasets, and crawlers. - A semantic enrichment and transformation engine, leveraging LLMs and tool-use to reason about and contextualize data. - A query engine that enables low-latency filtering and aggregation of enriched entities. - A workflow orchestration layer that lets users trigger actions in tools like Slack, Outreach, and CRMs via APIs or webhooks. - Prototype, iterate, and ship quickly: You'll have deep autonomy to test ideas, own systems, and ship features that impact customers directly. - Prioritize security and reliability: Handle sensitive customer data with best-in-class security practices and a strong foundation of reliability. - Elevate the engineering bar: We value clean abstractions, fast feedback loops, thoughtful testing, and excellent developer tooling. WHAT YOU BRING We’re still early and moving fast—ideal teammates thrive with autonomy, ambiguity, and high impact. You might be a fit if you: - Have 3+ years of experience building production-ready distributed systems and 1+ years of experience with production grade AI applications - Have worked with data-rich systems and are comfortable reasoning across messy and fragmented datasets - Are excited by LLMs, tool-use, and applied reasoning, and have built or experimented with intelligent agent workflows - Have a strong bias for action, and enjoy collaborating in small, nimble teams - Think in systems, debug across stacks, and don’t hesitate to dive deep when needed - Hold a high bar for simplicity, reliability, and product-minded engineering - Regularly ... (truncated, view full listing at source)