Netic Agent Product Manager at Netic owns the strategy and execution for a core product area focused on agent capabilities. The role requires technical expertise and customer empathy to drive product decisions and roadmap.
Responsibilities
As a Product Manager at Netic, you'll own the strategy and execution for a major area of our product suite: what our agents do, how well they do it, and how fast we can make them better. You'll work with engineering and research to ship, and with customers to understand the operational reality those agents run inside.
The surface area is large and moving fast. We need a PM with sharp technical instincts, real empathy for the operators running these businesses, and the judgment to make fast, high-quality calls without complete information. You should be as comfortable in an architecture debate as you are defending roadmap priorities to leadership.
Own the roadmap for a core area of the product, from strategy through launch and adoption.
Partner with engineering and research to ship agent capabilities that hold up in production, including the eval and quality bar that goes with them.
Go deep on how our customers actually operate, then turn what you learn into durable product decisions rather than one-off fixes.
Define what good looks like: set success metrics, instrument feedback loops, and use production data to decide what ships next.
Build the frameworks and processes that let the product team scale as we grow.
Qualification
Strong technical foundationFluent reasoning about APIsHands-on with the AI ecosystemObsess over the customerEvery second countsSweat the detailsThere are no blockersBe self-directedSeek and speak the truth
Required
Experience across product and engineering roles, including at least one year in an engineering role.
Strong technical foundation, with a track record of designing and shipping complex technical products alongside engineering.
Proven ability to drive a launch from concept to release, with real adoption or commercial impact to show for it.
Fluent reasoning about APIs, integrations, data models, and system design. You can read the code even if you don't write it day to day.
Hands-on with the AI ecosystem. You experiment with agents, models, and tooling yourself and stay current on what's changing.
