Job description
About Us and the Role
This job is not for your average Product Manager – we are a startup and we need someone who can fully embrace that. This is not about working yourself to exhaustion (we’re hybrid/remote and believe in balance), but about letting go of the comfort of a steady roadmap, a big UX research department feeding you insights, or a perfectly defined process for getting features out the door. Instead, this is about stepping into ambiguity, creating clarity, and knowing that every decision you make has a direct impact on our customers and our company. If that tradeoff appeals to you, keep reading.
We have a pretty killer technology called federated learning that enables data evaluation and experimentation without moving or sharing data – think of it like decentralized data science, where the workloads happen with the data owners instead of a central location. Our vision is that this technology fundamentally changes how companies build their AI data pipelines. Imagine being able to evaluate the predictive value of data before moving it, buying it, or exposing it. For insurance carriers, this means faster, safer, smarter model development across underwriting, pricing, fraud detection, claims, and marketing. We’ve already landed several top-tier carriers and data vendors, and we’re pushing hard to establish critical mass in this market.
The big vision, and the reason we’re all here, is that if we can establish ourselves as the way companies evaluate and integrate data for AI, we become the de facto platform for data experimentation in the age of AI.
About integrate.ai
integrate.ai is a data evaluation platform for quickly finding signals from noise while protecting sensitive data. It is like a dressing room where insurance carriers can try on data products from external vendors to measure the predictive value to their models, without the time, expense and risk involved in exchanging data. Typically increasing data security comes at the expense of speeding up innovation, but with integrate.ai carriers get more security and more speed. The platform works through integrate.ai’s proprietary federated learning technology, which ensures that the data stays inside the custodian’s firewall and is not visible to collaborators while performing a variety of data science workloads. Some of the top carriers in the world use integrate.ai for “signal hunting” across data vendors of all sizes, and across all cloud platforms and on-prem.
Impact and Responsibilities
As a Senior Product Manager (IC), you will:
- Own product outcomes end-to-end, from customer discovery and requirements development, through launch and iteration.
- Develop and own product roadmaps ensuring the prioritization of features and capabilities that deliver maximum value to users and drive adoption.
- Translate market insights and internal perspective into actionable specifications and compelling user journeys.
- Work with leadership across engineering, science, and go-to-market to develop a coherent and pragmatic product strategy.
- Establish product management best practices that strike the appropriate balance between speed and diligence in a stage appropriate manner.
The above might sound like a typical startup Product Manager role, but what makes things unique at integrate.ai is that you will also:
- Navigate technical complexity, from our federated learning and privacy enhancing data science methodologies, to the cross-organization, distributed execution architecture of our platform. You don’t need to be an expert in these technologies, but you should be comfortable engaging the relevant internal and external experts to support strategic product decisions.
- Be an effective aggregator and synthesizer of diverse information sources, spanning various customer stakeholder personas. Our platform is paradigm-shifting for our customers and the path to adoption comes with cross-persona complexities. Part of your job will be to build internal clarity to support rational decisions on which product investments to bet on vs reacting to stakeholder demands.
What We’re Looking For
We value diverse backgrounds and are open to candidates that are able to drive impact from a unique perspective. Treat the following list as guidance for what we’re looking for rather than a hard set of rules:
Skills and Mindset
- Strong grasp of product management fundamentals and an interest to mentor others
- You thrive under the energy and ambiguity of early-stage product development, continually updating hypotheses, testing them, and iterating at a fast pace
- AI-first mindset that balances curiosity with responsibility
- You focus on shipping and obsess over the success of users
- Comfortable interacting with engineers and machine learning scientists, with an ability to context switch between concepts related to outward facing UI all the way to the core technology stack
- Excellent written and verbal communication as the bedrock of how you drive clarity and alignment
Experience
- 5+ years in B2B SaaS product management, ideally spanning early PMF through growth stages
- Strong understanding of enterprise data and/or data science ecosystems
- Experience with the productization of ML/AI technologies
- Experience in insurance or financial-services data/model marketplaces is a big plus
Team & Culture Context
You’ll report to our CTO, Karl Martin, and work closely with a small, close-knit product management and design team. Our hybrid, async-friendly setup features frequent design sprints, weekly internal demos, and transparent docs everywhere – so autonomy, collaboration, and clear communication thrive.
We’re an equal-opportunity employer and welcome candidates of all backgrounds. Our thoughtful parental leave program, twice-yearly performance calibrations, and flexible work policies ensure everyone can thrive—whether you’re innovating a new feature or returning from leave.
Recruiting Process
- Recruiter / Technical Phone Screen
- 2–4 Functional Interviews (product strategy, user research, technical trade-offs)
- 2 Values/Culture-Add Interviews
- Final Conversation with Founder & CEO → Round-up decision within 48 hours—no waiting, no guesswork.
