Product Manager

ai71 builds
enterprise-grade AI for the organisations that underpin the real economy
: governments, banks, and large enterprises. We're rooted in the Middle East and Africa, where the demands on us are at their highest: sovereignty, on-prem, multi-lingual, and real regulatory weight. Those same demands are arriving everywhere, and
what holds up here travels
. Our work is grounded in a commitment to deploying AI securely, responsibly, and at scale.

Our flagship product is
Ask
, our agentic AI platform. It puts AI agents to work on an organisation's own knowledge, systems, and workflows: agents that reason through complexity, draw on the organisation's collective knowledge, and
complete real work rather than just answer questions
. Ask is
infrastructure agnostic and model agnostic
, so it runs inside a customer's existing stack and security perimeter, or in sovereign clouds, instead of forcing them onto ours. Today it's deployed across knowledge-heavy functions (legal, finance, HR, procurement) in
some of the most regulated environments in the world
.

We build Ask in
squads
: roughly a PM, three or four engineers, and a designer, each owning a slice of the product end-to-end and shipping it. A squad is small enough that the PM stays genuinely close to the work and carries real accountability for the quality of what ships.

We're hiring product managers for three kinds of ownership, and we're open on which one fits you:

Own a squad.Take one slice of the platform and make it excellent. You'll set the direction, write the PRDs, make the calls, and answer for the outcome.

Own a new bet.Some of the most valuable things we could build don't exist yet, and won't come from the current roadmap. This is 0→1 work: find the problem worth solving, prove it's real, and build the thing.

Go forward deployed.This is the sharpest end of the product. You sit with the customer, inside the ministry or the bank, and you turn the platform into something that works for them specifically. You see what actually holds up in production long before anyone else does, and the rest of the roadmap is downstream of what you learn. If you want the shortest possible distance between a decision you make and a real operation it changes, this is it.

We're hiring the person before the squad. We'll place you where your strengths meet our gaps, and we'll be straight with you about which gap that is during the process. The shape of the org will keep moving as the product does, and you should expect that.

This is deliberately not a role for someone who wants the strategy settled first. Ask runs inside air-gapped government networks, over messy multi-lingual corpora, for procurement-driven buyers betting real operations on us.A meaningful part of the job is deciding what's true, not executing against something already decided.The hardest questions on this platform are open right now, and whoever takes this role gets a real say in how they close.

Build things yourself.Prototype it, query it, script it. We expect PMs here to be
genuinely dangerous with an AI coding agent
, whichever one you like, and to bring a working artefact to an argument rather than a deck. The fastest way to settle a product debate here is usually to build the thing and look at it.

Own the outcome, end-to-end.Discovery, PRDs, prioritisation, shipping, and the metric it moves. Nobody here will hand you a spec, and nobody will thank you for delivering the wrong thing on time.

Own evals.This is one of the hardest and most important problems on the platform. Agent quality is not obvious from a demo, and "it looked fine when I tried it" is not a quality bar for a system running a ministry's legal review.
You'll define what good means for your surface, build the test sets and the judges that measure it, and wire them into how the squad ships
, so we know whether an agent works before a customer finds out it doesn't.

Stay ahead of the industry, and know what to build.This field moves faster than any roadmap. Capabilities we scope one quarter can ship free in an open-source release before we finish them, model releases reset what's possible every few weeks, and standards like MCP go from novelty to expected in months.
Knowing what to build, what to wrap, and what to adopt outright is one of the most consequential calls you'll make
, and it's a call you'll make repeatedly. That means knowing the landscape properly: the open agent frameworks, the observability and eval tooling, what the frontier labs…