Who We Are

Percepta’s mission is to transform critical institutions with applied AI. We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.

To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:

Forward-deployed expertise in engineering, product, and research

Mosaic, our in-house toolkit for rapidly deploying agentic workflows

Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more

Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day to day lives.

Percepta is a direct partnership with General Catalyst, a global transformation and investment company.

About The Role

Percepta's research org runs four parallel tracks — world modeling, forecasting, user modeling, and optimization — each feeding a shared pipeline: a world model compresses the operation, forecasters and user models score what happens next, and optimizers choose the best action. That structure only works if someone is actively running the machinery behind it — tracking where each track's research actually stands, where shared resources like compute are going, and whether commitments made to research leadership and customer-facing teams are on track.

Responsibilities

Own the operating rhythm of the research org: roadmap tracking, milestone check-ins, status reporting, and the recurring rituals that keep four research tracks legible to each other and to leadership.

Track dependencies across the four research tracks (e.g. a forecaster waiting on a world model, an optimizer waiting on a user model) and surface them proactively, rather than letting them surface late.

Manage allocation of shared infrastructure — compute, data access, and research engineering time across competing priorities, and escalate trade-offs rather than resolve them unilaterally.

Maintain a single, accurate view of commitments: what's been promised to customer-facing teams, what the research org has committed to shipping, and progress against both.

Coordinate the mechanics of getting research to external output where applicable — timelines, internal review, compliance — without owning the research content itself.

Build and maintain the systems (trackers, docs, dashboards) that let a fast-growing, deeply technical research team stay organized without adding process for its own sake.

Act as the connective tissue between Research Leads, Embedded Product Managers, and Applied AI Engineers by making sure the right people have the right information to make them.

What We're Looking For

Have prior experience as a program or technical program manager (TPM) supporting a research, ML, or other deeply technical organization with multiple parallel work streams.

Are comfortable reading and reasoning about technical research content well enough to track dependencies and risk, without needing to do the research yourself or set its direction.

Default to operational rigor: you build the tracker before someone asks for it, and you notice the dependency before it's blocking.

Are an excellent communicator who can translate status and risk between research leads, engineers, product managers, and non-technical stakeholders.

Are comfortable with ambiguity — this org and its processes are young, and you'll be building some of the operating model as you go, not inheriting a finished playbook.

Have a proven track record of keeping complex, multi-team technical work on track and shipping, measured by outcomes rather than activity.

Enjoy extreme ownership of the org's operational health, even when the underlying research isn't yours to direct.

We're working against an incredibly ambitious mission. It won't be easy but it will likely be the most fulfilling work of your career. If that excites you, let's chat, even if you don't meet all of the qualifications above.