Senior Technical Product Manager
Come join our Product team!
High velocity, high intensity, high trust, high bar, high impact, and a will to win.
If those words resonate deeply with you, this could be your next career move. We're seeking someone who leads with humility, pursues audacious goals, and is motivated by meaningful impact on people and the world.
At FutureFit AI, our core mission is to help more people get to better jobs faster and cheaper, with a specific focus on those facing barriers to opportunity. Our work helps resolve the growing issue of economic inequality, ensuring that no one is left behind in the future of work. Our AI-powered platform brings efficiency and insight to workforce development, replacing outdated systems and unlocking human potential at scale.
Ready to make an impact? Apply today.
Important note: Data shows that men typically apply when meeting 3/10 requirements, while women often wait until it's 10/10. We encourage you to apply if you see a strong (not necessarily perfect) fit.
Your Role
We're seeking a Senior Technical Product Manager to own the Customer Workflows domain - the full experience of how employers, recruiters, business service teams, and staffing agents experience and interact with our technology. This is not a traditional product management role. We are not looking for someone who has spent years in PM org hierarchies, handed off specs to designers, and waited for engineers to ship. We are building something different.
FutureFit AI operates in small, high-context teams, and every person on the product side is an active builder. This role is part product manager, part project manager, part prototyper, part researcher, and increasingly, part AI engineer. You will learn to manage fleets of agents, ship working prototypes with AI tooling, and collapse the distance between “I heard a customer problem” and “here is something you can use” from weeks to days.
You will operate at the intersection of product execution, platform architecture, and data intelligence: leading initiatives, owning your domain's roadmap end-to-end, and delivering against the craft bar across product-engineering-data collaboration.
What You'll Own
Employer & Recruiter Portal: Experience, performance, and activation across all recruiter-facing surfaces, including feature instrumentation and health metrics.
Business Service Workflows: End-to-end workflows powering business service operations on the platform.
Agentic Workflows: Tools, flows, and experiences that agents use to deliver value to employers and admins - increasingly augmented by agentic AI that handles routine steps and surfaces the next best action.
Agentic AI & data use cases: Surface and define agentic AI, LLM, search, and recommender applications - including candidate recommendations and automated business-service flows - translating them into clear requirements and the evaluation standards the data and engineering teams adopt.
AI-native execution: Use AI agents and LLM tooling as your default work layer - generating working prototypes, drafting test plans, synthesizing customer interviews - and turn what you learn into reusable processes others adopt. Know when to manage a fleet of agents and when to stop and involve humans.
Customer-centered discovery: Run continuous, lightweight research (direct interviews, session reviews, portal data analysis), structured Jobs-to-Be-Done discovery sessions, and fast prototyping to get something testable in front of real users before committing engineering capacity.
Product strategy & roadmap: Author and maintain quarterly roadmaps for the Customer Workflows domain, contribute to strategy discussions alongside the CPO, VP of Engineering, and VP of AI & ML, and connect employer/recruiter outcomes to ARR and mission goals - informed by competitor analysis, with a particular eye on agentic AI-native entrants.
Technical excellence: Own trade-offs across performance, scalability, cost, and speed; translate ADRs and engineering context into precisely scoped tickets; write PRDs with clear acceptance criteria, explicit edge cases, defined data requirements, and a testable definition of done; partner with engineering and analytics leads on data warehouse initiatives such as large-scale integrations and ATS work.
Cross-functional leadership: Be the go-to product partner for Product, Engineering, Data, Customer Success, and GTM in your domain; proactively brief Sales and CS before major releases; mentor peers on technical scoping, evaluation frameworks, agentic AI workflow, and discovery craft; and create reusable templates, decision frameworks, and playbooks that raise the quality floor.
Required Experience
Demonstrated ownership of a product area at a platform level - you can articulate the what, why, and trade-offs of every major decision in your domain with authority
A track record leading multi-quarter, cross-functional technical initiatives end-to-end
You are AI-native, not AI-curious: you already use LLMs, agents, and AI-assisted tools as your primary work layer - not occasionally, not experimentally - and you know what different models are good at, where they fail, and how to orchestrate them to get real work done
Strong technical depth: you can shape architecture discussions, evaluate agentic AI/LLM system quality, define evaluation frameworks, and scope non-functional requirements independently
Data fluency: you define OKRs and success metrics with precision, maintain a living metrics view, and drive data-informed decisions - not just report on delivery velocity
Proven cross-functional credibility: Sales, CS, and Engineering see you as a trusted partner, not a gatekeeper
Bonus Points
Experience with employer/recruiter, workforce, or B2B SaaS platforms
Fluency in employer and workforce development policy: WIOA service delivery, Workforce Pell, and Eligible Training Provider List (ETPL) dynamics
Familiarity with modern BI/analytics tooling (Looker, Snowflake, or equivalent)
Your Education
Your alma mater isn't our focus. Your grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately, you're our person.
Location
[CA/US Remote] We are open to candidates living anywhere in Canada or the US. For candidates living in Toronto, our office is conveniently located at 325 Front St West (a short walk from Union Station).
Travel Expectations
Although this role is remote, you may be expected to travel up to once per quarter for offsites and team gatherings.
Compensation
The base salary band for this role is USD $125,000 to $160,000 for candidates based in the US and CAD $125,000 to $165,000 for candidates based in Canada, regardless of location. As a remote-first company, we benchmark compensation to the national market for comparable roles at institutionally-funded startups, targeting the middle of the market. Bands are designed for the lifecycle of the role - where you enter the band reflects your applied experience and other criteria established by the hiring committee, with room to grow through the band as you grow in the role.
Hiring Journey
At FutureFit AI, our hiring process is designed to help you assess whether this role and our culture are the right fit based on your unique skills, mindset, and experiences. We move fast and work with intensity, so we want you to get a real sense of that from the start.
Each journey includes a mix of interviews and a performance challenge. For this role, that might look like:
Online Application
Initial Screen with Director of People & Culture
Interview with Hiring Manager
Performance Challenge
Final 1:1 Interviews
Final Decision
Generally, this entire process takes around 6 weeks, although the timing can vary due to specific candidate circumstances.
Ready to shape the future of work?
At FutureFit AI, we're not just building a company-we're transforming how talent and opportunity connect. Join our driven team united by a commitment to job seekers and the workforce ecosystems we serve.
Company Snapshot:
Team: 30-50 across US and Canada (hubs in NYC and Toronto)
Customers: Workforce development agencies and intermediaries, government agencies, employers
Industry: SaaS/AI technology
Funding: Bootstrapped 0-1, then raised funding led by JP Morgan
Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations
Our Core Principles
Be Curious
Drive to Outcomes
Raise the Bar
Speed Matters
Own It
We Over Me
Use of AI in Hiring
At FutureFit, we use artificial intelligence (AI) tools to make our hiring process more efficient, consistent, and equitable-never to replace human judgment. We use AI in the following ways:
Screening support: AI may help us compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input.
Interview support: In some interviews, we may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation.
Insights, not decisions: AI provides data points to support our team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request an accommodation.
© FutureFit AI All rights reserved, we are proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. We encourage people of different backgrounds, experiences, abilities, and perspectives to apply.