Designation: Principal Product Manager - QuilrAI Platform (2 positions) Experience: 8 to 10+ years Overview Quilr needs platform surfaces that are enterprise-grade on day one: reliable, low-overhead, deployable at scale, and safe to operate. This role is for an endpoint and browser platform expert who has shipped agents or extensions into real enterprise environments and understands the engineering and operational realities: performance budgets, OS constraints, rollouts, upgrades, and incident response. You will own the product outcomes for signal quality and enforcement reliability across the endpoint and browser, and you will be accountable for the deployment and lifecycle experience that customers judge you on. Characteristics Product CEO ownership (vision -> outcomes) Acts as the mini-CEO for their product area: understands customer and business goals, sets direction, and is accountable for results end-to-end (not just shipping tickets). Customer and 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 The endpoint agent and browser extension that generate signals and enforce policy: telemetry, controls, performance, privacy, deployment, upgrades, and reliability. You will define the platform contracts that upstream decisioning and downstream experiences depend on. Platform scope under this role • Endpoint agent and browser extension: signal collection and local enforcement hooks • Telemetry and connectivity: secure data pipeline, buffering, reliability, routing, data residency • Policy distribution and edge runtime: policy fetch/cache, local evaluation where needed, enforcement actions, fail-open or fail-closed, feature flags, rollback, kill switch • Lifecycle management: installers, MDM packaging, silent deploy, upgrades, compatibility, uninstall, device health • Admin and operability: device inventory, enrollment, health dashboards, diagnostics, support tooling, RBAC, audit logs • Integration foundations: connector framework, auth patterns, retries, health monitoring, normalized event schema • Identity and device context: users, groups, roles, device posture, session context, BYOD and guest handling • Telemetry schema governance: versioning, privacy and minimization, retention, sampling and throttling • Platform security hardening: tamper resistance, secure config storage, signing, integrity checks • Performance and quality: performance budgets, reliability targets, test harnesses, release gates • Cross-product contracts: consistent signals, policy formats, action semantics, evidence primitives across DLP, AI Security, and Decision Engine Key responsibilities • Own the roadmap for endpoint agent and browser extension capabilities, including telemetry coverage and enforcement controls. • Partner with engineering on secure telemetry pipelines, event schemas, and integrations with the decision engine and policy model. • Define and ship enterprise-grade deployment and lifecycle: installers, upgrades, compatibility, troubleshooting, staged rollouts, and rollback. • Set strict NFRs for performance overhead, stability, privacy, offline behavior, resilience, and safe failure modes. • Design enforcement UX and controls: warn, block, coach, approve, redact, quarantine, and evidence logging. • Drive operational excellence: observability, diagnostics, support playbooks, release quality gates, and incident learnings. • Align cross-functionally so behavior is consistent across endpoint, browser, SaaS, and gateways. Minimum qualifications • 8 to 10+ years of Product Management experience building endpoint, browser, networking, or security telemetry products. • Deep technical comfort with agents or extensions, OS constraints, performance overhead, secure data flows, and rollout safety. Quilr | Confidential Page 3 • Proven track record shipping enterprise deployment and lifecycle features that reduce friction and support escalations. • Strong operating rigor: scope control, release cadence, measurable NFRs, and quality discipline. Preferred qualifications • Experience with EDR, SWG, SSE, CASB, or DLP agents, including real-time enforcement and telemetry at scale. • Familiarity with enterprise device management and identity ecosystems. • Experience designing feature-flagged rollouts, migration strategies, and backward-compatible platform contracts.
Designation: Principal Product Manager - AI Security Experience: 8 to 10+ years Overview Quilr is building the security layer enterprises need to adopt GenAI safely, with real-time guardrails, evidence-grade logging, and operational workflows that security teams can run every day. This role is for an AI security expert who can translate AI risks into enforceable product capabilities, and who can partner with engineering to design telemetry, decisioning, and enforcement that works across users, apps, agents, and tools. You will own the core AI security experience from discovery through response, with a high bar for technical correctness, quality, and customer trust. 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 Security across AI usage discovery, AI asset modeling, interaction monitoring, guardrails, detections, risk scoring, and response workflows. You will define what is risky, what is allowed, and what happens next, and you will ensure the system is explainable and operationally usable. Key responsibilities • Own the AI Security roadmap across discovery, asset model, monitoring, guardrails, detections, scoring, and response workflows. • Translate AI risks into enforceable capabilities, including prompt injection, data leakage, policy violations, unsafe tool use, and anomalous usage patterns. • Partner with engineering on telemetry design, event schemas, risk scoring logic, explainability, and enforcement integration. • Define policy model and workflows for approvals, exceptions, user coaching, and security operations handoffs. • Set and enforce NFRs for latency, reliability, privacy, and evidence integrity across high-volume interaction data. • Drive customer discovery with CISOs, security teams, and AI platform owners to validate workflows and prioritize coverage. • Align Eng, Design, Docs, PMM, Support, and Sales on narratives, rollouts, and customer-facing outcomes. Minimum qualifications • 8 to 10+ years of Product Management experience building enterprise security or platform products (endpoint, SSE, identity, security analytics). • Highly technical PM who can partner directly with engineering and architecture on systems, APIs, data flows, and NFR tradeoffs. • Track record shipping products that balance precision, recall, usability, and operational trust at enterprise scale. • Strong writing and operating discipline: clear requirements, acceptance criteria, and quality bars. Preferred qualifications • Hands-on familiarity with LLMs, agentic workflows, RAG, tool calling, and AI governance patterns in enterprise settings. • Experience with SOC workflows, investigation tooling, and high-signal alerting at scale. • Experience designing explainable risk scoring or policy outcomes that customers can defend to leadership and auditors.
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.