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Staff Product Manager - AI Detection & Discovery

OneTrust

Atlanta, GAJobPosted 2 days agoStill listed 1 day ago

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At a glance

Compensation
No compensation found
Location
Atlanta, GA
Work Authorization
Not specified

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Job overview

Own product strategy for the Detection area across multiple related products, balancing delivery across the full product line. Set the Shadow AI detection strategy, discover unsanctioned models, applications, and agents, and route them into governance and remediation workflows.

Skills & qualifications

RequiredNice to have

Skills

AI DetectionAI GovernanceAI PrivacyEU AI ActNIST AI RMFISO/IEC 42001CSPMSSPMCASBIdPEDRSaaS ManagementBedrockAzure OpenAIVertex AILLM APIsOpen-Weight ModelsInference ServersFine-Tuning PipelinesTraining PipelinesVector DatabasesRAG ArchitecturesAgent FrameworksAPI EnumerationControl-Plane EnumerationLog TelemetryNetwork TelemetryOAuthIdentity AnalysisCode ScanningDependency ScanningEndpoint SignalsBrowser SignalsVendor QuestionnairesAttestations

Full job description

Strategy & Roadmap Own product strategy for the Detection area across multiple related products, balancing delivery across the full product line. Set the Shadow AI detection strategy: discover unsanctioned models, applications, and agents; attribute owners; risk-rank assets; and route them into governance and remediation workflows. Define and sequence the coverage roadmap across detection surfaces, weighing build vs. partner decisions, connector investment, and the risk retired by each incremental surface. Establish the detection taxonomy and definition of a “discovered AI asset,” bringing models, hosted endpoints, fine-tunes, RAG pipelines, agents, and embedded vendor features into one coherent inventory. Own the quality bar with measurable targets for coverage, precision, recall, time-to-discovery, and false-positive rate; make tradeoffs explicit. Identify adjacent opportunities, including continuous monitoring, AI bill of materials, third-party and supply-chain AI risk, and usage telemetry. Cross-Functional Leadership Lead geographically distributed engineering, design, data science, and detection research teams through ambiguous, discovery-heavy problems. Align with Product Marketing, Sales, and Partners on positioning and go-to-market in a category where buyers compare coverage claims. Partner with Security, IT, and Legal stakeholders—internally and at design-partner customers—to test detection signals against real enterprise adoption. Work with Ecosystem and Partnerships on cloud marketplaces and integrations with adjacent tools (CSPM, SSPM, CASB, IdP, EDR, and SaaS management) where telemetry can be shared rather than rebuilt. Technical & Domain Depth Serve as the Detection subject matter expert while building knowledge of adjacent AI governance and privacy products. Bring deep understanding of AI deployment, including managed model services (Bedrock, Azure OpenAI, Vertex AI), commercial LLM APIs, self-hosted open-weight models and inference servers, fine-tuning and training pipelines, vector databases, RAG architectures, and agent frameworks. Understand detection mechanics well enough to make hard approach decisions across API and control-plane enumeration, log and network telemetry, OAuth and identity analysis, code and dependency scanning, endpoint and browser signals, and vendor questionnaires or attestations where technical discovery cannot reach. Translate requirements from the EU AI Act, NIST AI RMF, ISO/IEC 42001, and emerging state AI laws into concrete detection and inventory requirements. Escalation & Communication Serve as the primary escalation point for the product line, de-escalating issues and communicating clearly from individual engineers to executives. Represent Detection strategy with customers, analysts, and prospects, and bring those insights back into the roadmap. Mentorship Informally mentor Product Managers and Associate Product Managers, sharing strategic and domain expertise. Raise the broader product organization’s bar for reasoning about AI systems, detection quality, and evidence-based prioritization.

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