Staff Product Manager - Bits Release

New Yorkfull timeOn Sitesenior$244k–$305kH1B: yes

Datadog Staff Product Manager at Datadog leading the creation of a new AI-native product that autonomously closes the loop on software behavior changes. Responsible for setting product direction, quality standards, and recruiting design partners.

Responsibilities

Set product direction for a new product family by defining the problems and desired outcomes, and partnering with engineering to find the narrowest first slice that proves the loop closes and delivers value to customers in phases.
Own the product decisions at every stage of the loop: what signal is trustworthy enough to trigger an automated change, which opportunities rank highest and with what confidence, what a proposed change must contain before a customer merges it, what evidence proves it worked, and what the system remembers for the next cycle.
Define the autonomy ladder and its limits, from suggestion, to draft, to auto-opened pull request, to auto-rollout, along with the controls, defaults, and audit trail customers need to rely on it. Some rungs stay off by design, and you own those decisions.
Set the quality bar for a product that is non-deterministic: build the evaluation sets with engineering, decide what "good enough to ship" means, and hold that bar when it moves a date.
Recruit the first design partners yourself, sit in their triage rotations, turn what you learn there into the roadmap, and keep talking to them after launch.
Develop and defend the sizing, impact, and cost-to-serve analysis that engineering leadership and pricing partners need to make resourcing calls, partnering with engineering on the unit economics of inference and the data platform and bringing that cost profile into packaging, metering, and pricing before launch rather than after.

Qualification

You have shipped AI productsYou treat evaluation as product workYou have a zero-to-one track recordYou read across staff engineersYou are collaborativeBackground as a software engineer

Required

You have shipped AI products, not prototypes: you have taken at least one AI-native product to production customers, and you can describe what it got wrong in the field and what you changed in response.
You treat evaluation as product work: you have built or commissioned evaluation sets, set the bar for shipping a model or prompt change, and held that bar under schedule pressure.
You are fluent in agent failure modes and design for non-determinism deliberately, accounting for confidence, reversibility, blast radius, review surfaces, and graceful failure.