Beacon is an AI transformation company. We own vertical market software businesses and we are rebuilding how they run and grow on one AI-native operating platform. Forward Deployed Engineers are where that platform meets reality. FDEs sit inside the pods with the vertical's product leader, own the customer, land the platform in real portco workflows, and carry each company's problems back to it. This is where our scarcest capacity is spent. We are hiring the leader who owns this function: the people, the doctrine, the allocation of capacity across pods, and the one number the model lives or dies on, labor per portco falling every quarter while the next deployment in a vertical gets faster than the last.
The doctrine: FDE, not consulting. An FDE delivers the outcome and compresses what they learned back into the platform, so the next deployment is cheaper. You hold the line: every engagement is scoped as a wedge with a written start, end, and deliverable; every deployment owes the platform a primitive, a playbook, or an agent workflow whose outcomes the platform can observe; every engagement leaves the portco's own engineers more capable. You are the person who notices when work is sliding toward one-off code and reshapes it.
Capacity allocation across pods. Roughly 1,000 engineering weeks a year across the portfolio. You decide, with the pod product leaders, where they go: named capacity on the anchors where revenue and transferable proof both agree, time-boxed and capped bets whose value is the evidence they produce, instrumentation on the cash engines, and nothing discretionary on the rest. Every item passes four gates before it gets an FDE: a business outcome in a number, an owner at the portco who wants it, a baseline we can already see, and a stack we can ship in this quarter.
The pod partnership. Each vertical runs one prioritized 1–N backlog, re-ranked weekly by the pod product leader and the FDE: they bring opportunity size and go-to-market timing, the FDE brings technical sequencing and what each deployment owes the platform. You make that mechanism real in every pod, so no FDE is setting their own goals and no FDE's work is invisible to the pod that depends on it.
The loop back to the platform. You are the intake for patterns coming out of the field and the strongest voice on what the rails are missing. Similar code taking shape at two portcos is your signal to pull a shared primitive; a workflow a GM would notice if we switched it off is your signal to ship it to the rest of the vertical.
The team. Hire senior generalists in Toronto and SF and grow them. Leads at Beacon are chosen for demonstrated upleveling of others, and that is the bar you hold your team and yourself to.
Player-coach. Carry one hard deployment yourself in the first two quarters. The role earns its standing by shipping.
Built and led a forward-deployed, solutions, or embedded engineering function at a company where the product was an AI or data platform; you have run the transition from "every engineer sets their own goals" to a team with a shared backlog and a shared standard, without losing the people.
Still a strong generalist engineer: comfortable in someone else's codebase within a day and has shipped LLM-native software in production with evals, autonomy gating, and outcome tracking. You can review an FDE's wedge and know whether it will compound.
Operator instincts. You read a P&L, you understand why a churn-save beats a feature launch this quarter, and you can sit across from a GM whose incentives are EBITDA-driven and land a deployment that borrows from the present to pay for the future.
Allocates ruthlessly and says so plainly. You have told a real business with a real GM that it is not where scarce engineering goes this quarter, kept the relationship, and been right.
Writes clearly and works transparently: async, in public channels, decisions documented where anyone can find them. At Beacon the wedge memo, the GM update, and the post-deployment retro are the work.
Bonus: Palantir-style FDE background; private equity or holdco operating exposure; time inside vertical SaaS; experience taking a portfolio of legacy stacks onto shared rails.
Our Values at Beacon Software
Humility: We acknowledge that the path to getting to the right answer involves being wrong along the way. We have strong beliefs which are weakly held. We actively seek new ideas and believe we can learn from anyone at any time.
Honesty: We are truth seeking in our approach to business problems. Business is a repeat game and we believe that human relationships generate alpha. We understand that trust is earned over a lifetime and can be lost in an instant.
Hunger: We play to win. We hold ourselves to high standards and will not be outworked. We take pride in having a deep sense of responsibility to ourselves, each other, our partners, and our customers. We believe to whom much is given much is expected.
Horizon: We seek to build a generational software company. This will take decades. We manage our expectations and those of our partners to take advantage of the 8th wonder of the world - compounding growth.
How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Beacon Software uses Artificial Intelligence and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role.
AI does not make hiring decisions: Every application is reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate.
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