Engineering Manager & Product Lead (Float Intelligence)

• Float is hiring a Founding Lead to own and accelerate Float Intelligence end to end, across the technical foundations, the data, and the product experiences, all under a single mandate. Float Intelligence is how we bring agentic AI finance to every business in Canada: a product that does the finance work our customers do by hand today, coding transactions, chasing receipts, checking spend against policy, and gathering invoices out of inboxes and vendor portals. We shipped the first version this year and it worked. Now we are building the rest of it, and we are building it fast
• You would lead a small, fast-moving team of product engineers and data/ML engineers, reporting directly to the Head of Product. This is intentionally a hybrid seat across Engineering and Product leadership. You own the roadmap for what gets built, and you make the technical calls: model choice, evaluation, what has to be deterministic, and what a launch is gated on. The team ships into other product teams’ surfaces and builds net-new surfaces that put AI directly in front of customers
• This is a true end-to-end owner role. The people who do best here are ex-founders and highly capable technical leaders with strong commercial product taste, opinionated about both what to build and how to build it, and drawn to the highest-leverage, most cutting-edge AI work across Float’s entire product surface
• Leading, growing, and developing a small team of product engineers and data/ML engineers
• Owning the roadmap for Float’s AI experiences alongside the Head of Product, including proposing new bets
• Taking AI products from zero to one, from exploratory proofs of concept through to the experiences that reach customers at scale
• Making the technical calls: model and LLM approach, evaluation design, and the infrastructure for scale, latency, and inference cost
• Building the shared platform layer, where required for: extraction, evaluation, observability, agent and prompt frameworks, and data pipelines, that other product teams build on rather than rebuild
• Equipping internal product teams with the AI models and engines they need to ship the experiences they want, and building new customer-facing surfaces that expose those experiences directly
• Partnering with the product managers whose areas these experiences ship into, so each one lands well and ownership is clear afterward
• Deciding what to stop, since exploratory work only pays off when the things that are not working get killed quickly

Benefits

• Competitive coverage of medical, dental and vision insurance for employees
• Education & learning stipend for personal growth and development
• Flexible vacation time
• Work from home stipend to help you succeed in a remote environment- Hands-on experience building and shipping AI or LLM-backed products to real users — not prototypes or internal experiments
• You Constantly Learn and Grow. You’re hungry to improve your craft and open to feedback. You bring a growth mindset to everything you do
• You Put Customers First, Always. You care deeply about delivering meaningful value. Whether you’re building internal systems or customer-facing features, you’re always thinking about how to make life better for our users
• You Act Like an Owner. You take responsibility for outcomes, step up to challenges, and seek solutions proactively—doing what’s best for the business, not just your role
• Nice to have: experience fine-tuning models, or a data science or ML engineering background
• A track record of building something 0→1, whether as a founder, an early engineer, or the person who started a product line inside a larger company
• You Think Big and Move Fast. You’re energized by building from 0 to 1. You’re not afraid to challenge the status quo, experiment quickly, and learn as you go
• You Raise the Bar. You care about doing things well and efficiently. You balance speed with rigor and always look for ways to improve how we work
• Product instincts strong enough to own a roadmap: choosing what to build, sequencing it, and defending what you left out
• 2+ years managing engineers, ideally including people whose specialty is not your own
• 7+ years in software engineering, including time at a company with a strong engineering culture where you reached a senior or staff level
• Past experience building 0→1 products or founding a software business
• Comfort working across other teams’ surfaces and getting alignment without formal authority
• You Win as a Team. You’re a generous collaborator who values communication, context, and shared wins. You lift others up and help make the team stronger
• Real depth in the parts that make AI products work in production: evaluation design, infrastructure at scale, latency, and managing inference cost with vendors