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Float is Canada's intelligent financial operating system, combining modern financial services and software to help businesses spend, save, and grow. Trusted by over 7,500 Canadian companies, Float provides corporate cards, automated expense management, bill payments, and high-yield accounts. Recently closed an $85M Series C and is backed by top-tier investors including Inovia Capital and Goldman Sachs Alternatives.
You'll be hired as a Senior Corporate Engineering & AI Systems Engineer to build the internal platform that enables every team member to scale themselves through AI automation. This role owns three core systems: (1) the harness—a secure, governed layer connecting AI models to Float's internal systems with identity-aware access, tool connectors, guardrails, and audit trails; (2) the platform—a paved road letting any employee compose, run, and share automations; and (3) background agents—always-on workers that triage queues, reconcile data, and draft responses, escalating to humans when judgment is needed.
Key responsibilities include building authenticated, scoped, auditable connectors and MCP servers linking LLMs to Slack, Google Workspace, Salesforce, NetSuite, Zendesk, and Float's product; shipping multi-step background agents with tool routing, memory, retries, human-in-the-loop approvals, and audit trails; building a skills-sharing layer that turns one team's automation into company-wide capability; embedding with teams to map workflows and turn ambiguous problems into shipped systems; and owning governance with Security and Risk around non-human identity, scoped permissions, prompt-injection defense, and privacy guardrails.
You bring 7+ years of software engineering including internal platforms that measurably increased team output, 1–2+ years building LLM-powered systems in production with real users and reliability requirements, strong production Python and/or TypeScript with full-stack capability, deep practical knowledge of agentic systems (tool use, orchestration, context engineering, structured outputs, memory, background-agent patterns), an eval-first mindset with success metrics and observability built in, integration and auth expertise across enterprise SaaS (REST, webhooks, OAuth/OIDC/SAML), security and governance judgment for financial services, workflow-discovery skills to translate non-technical team processes into automation specs, and AWS cloud fluency with CI/CD comfort. Bonus experience includes agent frameworks (Claude Agent SDK, OpenAI Agents SDK, LangGraph, Pydantic AI), MCP server design, and durable-execution or workflow-orchestration patterns.
