Staff Product Manager, AI Agents & Assistant

Dashlane•New York, NY

1d•Hybrid

About The Position

Dashlane is hiring a Staff Product Manager for Agentic Capabilities to own the vision, strategy, and roadmap for making Dashlane an interface for AI agents and assistants serving consumers and businesses. The role focuses on enabling people to delegate valuable tasks to agents through Dashlane and building the trust companies need to let their teams do the same. This is a Staff-level individual-contributor, 0-to-1 role working alongside senior engineers in a field where standards are still emerging. The product manager will bring strong familiarity with the modern AI landscape and sound judgment about what agents can and cannot be trusted to do. The role connects consumer and business needs, establishes trust commitments and product controls, builds ecosystem relationships, and aligns internal teams around a shared plan. Dashlane uses a hybrid work model. Teams collaborate in the office on Mondays, Tuesdays, and Thursdays, with Wednesdays and Fridays offering more flexibility for focused work.

Requirements

At least 8 years of product management experience.
Experience owning an authentication, security, identity, or permissions-heavy product.
At least one product taken from zero to market with measurable adoption, revenue, or retention success in an emerging market.
Technical fluency with OAuth, passkeys, sessions, and browser extensions sufficient to follow token-flow discussions and identify potential failure points.
Strong familiarity with LLMs, assistants, and agentic workflows, and the ability to reason about AI capabilities and limitations from product and customer perspectives.
Working knowledge of agent operation, including tool use and standard tool interfaces, browser-driving agents, context retention and loss, and ways agents can be tricked.
A track record of interpreting a fast-moving market and turning its signals into strategy acted on by leadership.
Experience running 0-to-1 discovery with small samples and incomplete information, and defining success through customer outcomes rather than shipped features.
AI-native working practices, including building prototypes with AI, using it for discovery synthesis, chaining agents into workflows, and demonstrating how AI has changed product work.
Strong written and verbal English communication skills, including writing clear problem statements, one-pagers, roadmap rationale, and external category narratives.
Legal eligibility to work in the country of application.

Nice To Haves

Systems-thinking and platform experience, including shipping a platform, API, integration product, or partner ecosystem with describable outcomes.
Experience with products serving both individuals and businesses, and the ability to identify how decisions in one context affect the other.
Comfort acting amid ambiguity and making decisions with incomplete information.
Collaborative, low-ego approach, including willingness to defer to others’ expertise while expressing a clear point of view.
Intellectual honesty, transparent communication of results, openness about failures, and a habit of documenting evidence that would change a decision.
Security threat-modeling instincts covering prompt injection, phishing, malicious extensions, and the risks of compromised agents.
Commitment to human accountability for consequential AI decisions and to evaluating AI before release.

Responsibilities

Set and defend a product point of view on how AI agents and assistants should interact with credentials and other information protected by Dashlane, and turn it into strategy, positioning, and a multi-year plan.
Track developments across agent makers, assistants, browsers, identity vendors, and password managers; assess readiness of emerging capabilities and standards, and define when to act.
Lead discovery into the tasks people delegate to agents at home and at work, identifying demand and barriers to adoption.
Connect consumer and business product needs, translating individual use cases into visibility and controls for IT and Security teams, and identifying cross-audience impacts of decisions.
Define Dashlane’s trust commitments regarding what agents and models can see and do, and ensure product decisions and releases uphold them.
Develop durable product controls for agent use, such as limits, approvals, records, and revocation.
Determine which agent makers and platforms to invest in and on what terms; build relationships and technical rationale with partners and services used by agents.
Lead Dashlane’s contribution to standards for agent sign-in and acting on someone’s behalf, ensuring positions reflect customer needs and product direction.
Set and report adoption, repeat-use, and trust baselines and targets, including time to first approved agent login, decision time for agent requests, and recovery from failures.
Align Design, Engineering, Security, Legal, Sales, and Marketing around a plan; establish team operating rhythms and decision frameworks, and clarify ownership.
Within 90 days, turn early engineering work into a shared problem view, a trust model backed by Security and Architecture, proposed success targets, and a category point of view shared with leadership.
Within six months, deliver agentic value to real users, establish recurring engagement, and identify who benefits most initially.
Within 12 months, demonstrate continued use and impact on plan choice and retention; define an initial company offering and next steps; and secure leadership backing for a B2B and B2C agent and assistant vision and roadmap.