# Senior / Staff Engineer, Applied AI (Float Intelligence) **Company**: Float **Location**: Toronto, Ontario **Work arrangement**: remote **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Finance **Apply**: https://jobs.ashbyhq.com/float/fb8e1bd3-b03b-4317-a53f-fcd66e76c013?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_8884b579-7b7 ## Description Float is building an agent that works as a chief financial officer for every Canadian business. You would join the small team building the foundation for it, with a blank slate and a direct line to the product teams that will build on what you make. You’ll have the best seat in the house on how to apply the frontier to real finance problems: taking raw model intelligence and turning it into durable, scalable, useful products. The team sits between the model providers, Float’s product teams, and the customers whose finances we run, building the harness , memory, skills, tools, evals, observability, distribution channels , that every agent at Float runs on. This is a zero-to-one position. You will build the core pieces that let agents act reliably in production, and the interfaces and channels customers reach them through, then scale them across Float’s products. **Responsibilities** - Ship agents that save customers real money and time. Take them from the first prototype to production at scale, and own the outcome once they’re live. - Build the unified harness. Context management, capabilities and tool use, evaluation, monitoring and observability , the layer every agent at Float runs on and scales through. - Make agent actions safe to trust with a company’s money. Permissions, approvals, audit trails, and clear behaviour when the agent is uncertain or wrong. - Define what good looks like and measure it. Offline evals, production monitoring of agent decisions, and the loop that turns incidents into improvements. - Build the interfaces agents are delivered through. Chat, generative UI, and multiple channels at once. - Make product teams faster. Partner with them so they can launch their own agent capabilities on the harness without rebuilding it. - Stay on the frontier. Track models, inference and context management, and rework what we’ve built when a better approach appears. **Requirements** - Experience building and shipping agents or LLM-backed systems to production, and running them there: monitoring, improving and scaling them. Typically 5+ years of software engineering for Senior, 8+ for Staff, with a track record of technical leadership across teams at Staff. - Depth in one of two areas: full-stack product engineering for agentic experiences, or backend engineering for LLM pipelines and agent infrastructure. - Hands-on, current knowledge of frontier models, inference and context management, and opinions about what works. - Comfort giving agents capabilities and context and then observing them, rather than specifying every step. - Experience at more than one company stage, or in a company growing quickly, with major ownership and impact. - A habit of building things nobody asked you for, and finishing them. - Curiosity, and the willingness to start over when the field moves. **Benefits** - Competitive compensation, equity options, and benefits - Hybrid work model: we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters For more fresh new jobs, check out [yubhub.co](https://yubhub.co/). ## Skills ### Required - agent development - LLM pipelines - context management - evaluation frameworks - full-stack product engineering - backend engineering ### Nice to have - fintech - payments - regulated products - evaluation frameworks for LLM systems --- Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/float/fb8e1bd3-b03b-4317-a53f-fcd66e76c013?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)