Product Manager - Exposure Management

Department Icon Data Science Analytics & Machine Learning
Posted: 1 month ago
0-1 years
Cochin / Kochi / Ernakulam, Kerala
Data Science Analytics & Machine Learning
work from office
Full Time
Closes 21 Nov 2026

Posted: 1 month ago
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Job Description

Role purpose:

Do you want to help organisations find and fix their most critical exposures before attackers do At Prevalent AI, our Exposure Management application sits on top of our Data Fabric platform as our flagship application — unifying asset, vulnerability, identity, and control data into a knowledge graph of interconnected security entities. Powered by agentic AI prioritization, it delivers contextual, actionable intelligence that shifts clients from reactive vulnerability management to proactive, pre-emptive risk reduction aligned with Continuous Threat Exposure Management (CTEM).

As Product Manager for Exposure Management, you will own the strategy, roadmap, and growth of the Exposure Management application — from attack surface visibility and risk-based prioritisation through to remediation workflows, attack path mapping and measurable exposure reduction. You will work closely with clients, go-to-market teams, and engineering to identify the highest-value opportunities, sharpen the applications differentiation, and unlock cross-sell within existing accounts. You will balance near-term delivery with long-term vision — delighting clients today while contributing to a platform where clients create and bring their own agents. If youre passionate about turning complex exposure data into decisions that matter — join us.

Key accountabilities:

Strategy & Vision

  • Define and own the product vision and roadmap for the Exposure Management application, ensuring alignment with client outcomes, business goals, and the evolving threat landscape.
  • Guide the development of high-level features, Epics, and use cases — grounded in real-world security workflows and informed by AI-powered knowledge graph insights.
  • Leverage market intelligence, client feedback, and competitive analysis to prioritise the roadmap and identify opportunities for innovation across the CTEM lifecycle.
  • Contribute to the portfolio-level strategy for Data Fabric Applications, ensuring Exposure Management reinforces a coherent platform proposition.

Client & Market

  • Partner with Sales, Marketing, and Client Solutions teams to ensure the Exposure Management application remains client-focused and keeps pace with the evolving market.
  • Translate complex exposure and vulnerability management challenges into actionable, outcome-driven product features that demonstrably reduce client risk.
  • Identify pain points and innovation opportunities through deep client engagement and data analysis.
  • Work closely with Sales and go-to-market teams to shorten deal cycles, strengthen sales tooling, and unlock cross-sell opportunities within existing accounts.

Engineering & Delivery

  • Partner with Engineering and Product Development teams to ensure the design and implementation of use cases aligns with client and market demands, whilst remaining deliverable and maintainable.
  • Provide knowledge transfer and guidance to Data Analysts, Engineers, and Data Scientists — ensuring the broader development team understands the client challenges and security problems the applications address.

Go-to-Market

  • Collaborate with Sales and Marketing teams to inform the creation of product marketing material and support go-to-market execution.

Leadership & People Management

  • Lead, manage, and develop a team of Product Owners, providing clear direction, regular feedback, and support for their professional growth.
  • Set objectives for the Product Owner team that are aligned with the broader product strategy, and hold regular 1:1s and performance reviews.
  • Foster a high-performing team culture built on accountability, collaboration, continuous improvement, and agile ways of working.
  • Champion agility, iterative learning, and innovation across product and engineering teams.

Skills and Experience:

Essential

Product Management

  • Proven experience in product management, with a track record of owning strategy, roadmap, and full lifecycle delivery of complex technology products.
  • Deep understanding of agile development and end-to-end product delivery, with strong prioritisation skills focused on client value and business impact.
  • Skilled at balancing immediate client needs with long-term product vision, using data, market research, and competitive analysis to drive decisions.

Cybersecurity Domain

  • Strong understanding of threat and exposure management, including vulnerability management, attack surface management, identity security, and risk-based prioritisation.
  • Familiarity with frameworks such as CTEM, and a practical understanding of attack surfaces, attack paths, misconfigurations, control gaps, and shadow IT.
  • Experience working with or alongside vulnerability management or security operations teams — understanding how practitioners assess, prioritise, and remediate exposures in practice Hands-on familiarity with exposure management tooling — such as vulnerability scanners, EASM/CAASM platforms, attack path or exposure graph engines, and risk scoring approaches — including key operational pain points and workflow patterns.

AI & Data

  • Demonstrable experience shipping AI-powered products, with a working understanding of how ML models, LLMs, and AI-driven insights are integrated into product experiences.
  • Experience translating complex data and AI-driven outputs into actionable, client-focused product features that drive measurable security outcomes.

Leadership & Communication

  • Experience leading and developing product teams, including line management of Product Owners.
  • Confident communicator, adept at presenting to senior stakeholders and leadership.
  • Proven ability to build strong relationships across cross-functional teams including Engineering, Sales, and Client Solutions.

Desirable

  • Experience working with knowledge graph concepts and entity-relationship data modelling — understanding how interconnected data can be used to surface contextual security intelligence.
  • Familiarity with agentic AI frameworks or AI-assisted workflows in a security operations context.
  • Experience building use cases on top of a shared data platform or data fabric architecture.
  • Familiarity with vulnerability intelligence and scoring standards — such as CVSS, EPSS, and KEV — and how they inform risk-based prioritisation.
  • Experience working in or alongside a managed security service, with an understanding of how client-facing delivery shapes product requirements.
  • Familiarity with the Databricks ecosystem or similar data platforms.

Education:

  • B.Tech in Computer Science, or a related field, Bachelors degree in Business Administration
  • Certification in Product Management or Agile methodologies (e.g., PMI-ACP, CSPO) is a plus

Skills

CspoData AnalysisImplementationAiMlLlmsAgenticAgentic AiKnowledge GraphDatabricks

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About Company

Prevalent AI is a technology company specializing in artificial intelligence, machine learning, and data analytics solutions.

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