Principal Product Manager - DLP

Designation: Principal Product Manager

Experience: 8 to 10+ years

Overview

Quilr is building an AI security and AI-powered DLP platform for enterprises that cannot afford

ambiguity, weak enforcement, or unverifiable audit trails.

This role is for a DLP expert who has shipped policy-driven security products in production,

understands how buyers operationalize them, and can partner deeply with engineering to deliver

precision, scale, and enterprise-grade reliability.

You will own outcomes across discovery, policy, detection, enforcement, workflow, and evidence, and

you will be accountable for reducing customer risk in real environments - not just shipping features.

Characteristics

Product CEO ownership (vision -> outcomes)

Acts as the mini-CEO for their product area: understands customer + business goals, sets direction,

and is accountable for results end-to-end (not just shipping tickets).

Customer + market leadership

Deep customer empathy and discovery chops: talks to users, synthesizes feedback, anticipates needs,

and translates insights into a clear roadmap and crisp problem statements.

Technical + engineering-first execution

Highly technical PM who can work shoulder-to-shoulder with engineering/architecture: understands

systems, tradeoffs, APIs/data flows, NFRs, and can drive high-quality solutions without hand-holding.

Operating rigor (plan, scope, risk, quality)

Runs execution like a GM: prioritization, scope control, delivery cadence, metrics, escalation with

mitigation plans, and a high bar for quality (AC/DoD/NFRs). Cuts waste and prevents quick hacks

becoming permanent.

Cross-functional alignment + influence

Connective tissue across Eng/Design/Docs/PMM/Support/Sales/Leadership: aligns stakeholders,

drives decisions, communicates clearly, and leads through influence - especially in fast-changing

environments.

What you will own

AI-powered DLP across GenAI and SaaS surfaces: discovery, classification, policy, detection,

enforcement, workflows, and evidence-grade auditability. You will define the product model and

decision boundaries that make enforcement consistent and defensible, and you will drive the

operational workflows that security teams rely on.

Key responsibilities

Define and ship the DLP roadmap for AI and SaaS data movement, tied to customer risk and business

outcomes.

Drive continuous discovery with CISOs, security architects, GRC, and IT to turn pain into crisp problem

statements and measurable requirements.

Partner with engineering on architectures for classification pipelines, policy evaluation, enforcement

planes, and telemetry at scale.

Specify and drive NFRs: latency, throughput, reliability, privacy, data residency, false positive

management, and evidence integrity.

Design investigation and response workflows: triage, alerts, case management, approvals, exceptions,

escalation, and reporting.

Ensure high-quality releases with strong AC/DoD, testability, rollout safety, and clear rollback paths.

Partner with PMM and field teams on positioning, differentiation, and enterprise readiness for regulated

environments.

Minimum qualifications

8 to 10+ years of Product Management experience building enterprise security products, with

meaningful depth in DLP or data security (SSE, CASB, endpoint DLP, SWG, or security analytics).

Proven track record shipping policy-driven products used by enterprise buyers, including workflows for

approvals, exceptions, and audit.

Strong technical fluency: APIs, event pipelines, identity context, endpoint and browser telemetry, and

SaaS integration patterns.

Strong writing and operating discipline: crisp requirements, measurable acceptance criteria, and

non-negotiable NFRs.

Preferred qualifications

Experience with detection engineering concepts, policy evaluation engines, data classification, or data

lineage.

Experience with regulated customers and compliance-driven requirements (BFSI, healthcare, public

sector).

Familiarity with GenAI data risks, prompt and response flows, and enforcement across AI assistants

and SaaS apps.