About the Role

This might just be the most interesting internal AI opportunity in Canada (if we do say so ourselves)!

We're hiring a Senior Corporate Engineering & AI Systems Engineer to build the internal platform that lets every Floater scale themselves - so each person feels like a team of ten.

You'll own three things: the harness (the secure, governed layer connecting AI models to Float's internal systems, with identity-aware access, tool connectors, guardrails, and audit trails), the platform (the paved road that lets any Floater compose, run, and share automations), and the background agents (always-on workers that triage queues, reconcile data, and draft responses while Floaters sleep, escalating to a human when judgment is needed).

This is not an evaluate-some-tools-and-write-a-policy role - you'll be in the room when a team describes a problem, and shipping the fix, often the same week.

What You'll Do

• Build the harness: authenticated, scoped, auditable connectors and MCP servers linking LLMs to Slack, Google Workspace, Salesforce, NetSuite, Zendesk, and Float's own product.
• Ship background agents that run multi-step workflows end to end - with the tool routing, memory, retries, human-in-the-loop approvals, and audit trails that make them trustworthy in fintech.
• Build the skills-sharing layer that turns one team's automation into everyone's capability, and drive the adoption that makes it worth building.
• Embed with teams to map how they work and turn ambiguous problems into shipped systems - defining evals before you build and instrumenting reliability and cost as you go.
• Own governance with Security and Risk: non-human identity, scoped permissions, prompt-injection defense, and privacy guardrails that enable rather than block.

About You

You're a builder first - you've seen that the highest-leverage engineering right now multiplies everyone else, and you want to do it somewhere with real ownership and zero red tape.

• 7+ years of software engineering, including internal platforms or tools that measurably increased team output.
• 1-2+ years building LLM-powered systems in production - real users, real reliability requirements, not prototypes.
• Strong production Python and/or TypeScript, plus the full-stack range to ship a usable interface when a workflow needs one.
• Deep, practical knowledge of agentic systems: tool use / function calling, orchestration, context engineering, structured outputs, memory, and background-agent patterns.
• An eval-first mindset - success metrics before you build; observability, guardrails, and cost controls as part of the system.
• Integration and auth chops across an enterprise SaaS stack: REST, webhooks, event-driven patterns, OAuth / OIDC / SAML.
• Security and governance judgment - scoped, auditable access, human-in-the-loop design, and a clear sense of what an agent should never do in a financial company.
• Workflow-discovery skills: sit with a non-technical team and turn how they work into an automation spec with measurable targets.
• Cloud fluency (AWS) and comfort with CI/CD.

Bonus points if you have:

• Experience with agent frameworks and SDKs (Claude Agent SDK, OpenAI Agents SDK, LangGraph, Pydantic AI), and with MCP server design specifically.
• Durable-execution or workflow-orchestration experience (e.g., Temporal) for reliable long-running agents.
• Corporate-engineering / IT-systems depth: identity providers (Okta, Google Workspace admin), ITSM and approval workflows, or SaaS administration at scale.
• An iPaaS / automation-platform background (Workato, n8n, Zapier, Retool), with clear opinions on when no-code is the right answer.
• Fintech or other regulated-industry experience, and a working sense of what SOC 2 / ISO 27001 mean for AI systems.
• Power-user habits with AI coding tools (Claude Code, Codex, Copilot) - you'll be building the environment that makes everyone else one too.

This may not be the role for you if:

• You prefer a stable, predictable routine - this space reinvents itself quarterly.
• You need detailed specs handed to you. Here you'll write them, often after discovering the problem yourself.
• You want to build AI systems without talking to the humans who use them.
• You'd rather perfect a system for months than ship something valuable this week and iterate.
• Being accountable for security and governance trade-offs, not just feature velocity, sounds like someone else's job.

Flexible Work Model

Float is Toronto-based with a hybrid model: in-office collaboration days, plus occasional in-person time for workflow-discovery sessions. Remote candidates within Canada considered, with occasional travel to Toronto.

Why You Should Join

• Work at one of Canada's fastest-growing fintech companies
• Make a real impact in a high-autonomy, high-growth role
• Collaborate with an ambitious and supportive team
• 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

In Short

At Float, you'll thrive if you're bold, curious, and eager to make a real impact. We're building something special-and having a lot of fun along the way. If you're excited to build, grow, and win together, we'd love to meet you.