Product Management Lead

Magnet Forensics develops digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices. The Lead Product Manager will drive the strategy, discovery, execution, adoption, and growth of a core examination and analysis product, including AI-native agentic experiences, while collaborating with customers and cross-functional teams.

Responsibilities:

• Drive the product discovery of the evolution of one of Magnet’s core products: execute upon the product vision, roadmap, and success metrics for the examination and analysis product, including agentic experiences within it
• Own the outcome like a GM: Own the success of your area end to end: strategy, roadmap, positioning inputs, pricing inputs, and the business results. Set the bar for what "good" looks like and be accountable for whether it landed, not just whether it shipped
• Build experiences that ship: Design and deliver product that examiners and investigators actually use in casework, from core AXIOM workflows through AI-assisted capabilities (copilots, human-in-the-loop review, retrieval, automation). Production grade, reliable, and defensible
• Build for trust and defensibility: In forensics the output has to hold up. Define verification, transparency into how a result was produced, reversibility, escalation paths, and auditability so users can defend the work downstream. Treat this as an enforced constraint, not an aspiration
• Run continuous discovery: Engage customers and prospects through interviews, onsite visits, lab ride-alongs, workshops, and discovery sessions. Map opportunities to solutions, validate before building, and keep a living view of unmet needs
• Decide with data: Instrument every experience, define the metrics that matter, and run a disciplined experimentation practice (A/B tests, funnels, cohort analysis) so decisions are grounded in evidence, not opinion
• Drive adoption and growth: Own activation, onboarding, and the path to habitual use. Reduce friction, design for time to value, and build the loops that turn usage into expansion and retention. Partner with go-to-market and growth to convert capability into usage, usage into value, and value into revenue
• Master the market: Develop deep expertise in DFIR (Digital Forensics and Incident Response), competitive dynamics, customer workflows, and where emerging technology (including AI) meaningfully changes how investigations get done. Use it to inform strategic bets
• Navigate competing priorities: Make thoughtful tradeoffs across scope, quality, trust, and timelines while staying aligned to strategic objectives
• Drive clarity: Break ambiguous problem spaces into structured, actionable plans that align leadership and let teams execute with confidence
• Lead strategic visibility and alignment: Track the metrics that signal success and give clear, outcome-focused updates to executives and cross-functional partners
• Collaborate across teams: Partner with engineering, UX, data science, and peer PMs to deliver experiences that are intuitive, consistent, and aligned to key personas
• Influence cross-functionally: Build strong relationships with GTM, customer success, support, and leadership to drive alignment and optimize results
• Work AI-natively: Default to AI across your own workflow (discovery, research, analysis, drafting, prototyping) and model AI-native ways of working that raise the bar for the wider product team
• Travel: 5-15%

Requirements:

• You use AI as a default part of how you work, not an occasional assist
• You are fluent with current AI tools and prompt engineering for research, discovery synthesis, competitive analysis, drafting (PRDs, specs, user stories), data analysis, and rapid prototyping
• 7-10 years in product management
• Demonstrated track record driving product adoption, activation, retention, and growth
• Fluent with product analytics and experimentation
• You instrument what you build and let metrics guide tradeoffs
• Skilled in continuous discovery and validation techniques (customer interviews, opportunity-solution mapping, Jobs To Be Done)
• Able to partner closely with engineering and data science on AI system design (models, retrieval, evaluation, latency, cost) and to reason about tradeoffs across complexity, scalability, trust, and customer value
• Skilled at interpreting market data, customer insight, and usage metrics to drive decisions
• Strong collaboration skills and the ability to communicate effectively with both technical teams and executive stakeholders
• Act as the champion for your product, anticipating challenges, removing obstacles, and driving momentum to meaningful business results
• ideally with enterprise SaaS & GovTech experiences
• ideally in a product-led motion
• Industry experience in Digital Forensics, Incident Response, cybersecurity, or other regulated, high-trust domains
• Hands-on experience with modern AI tooling and patterns (LLM orchestration, RAG, agent frameworks, evaluations, guardrails)
• Familiarity with AI governance, safety, or responsible AI practices in a product context
• Experience building within On-Premise and Hybrid Deployment models
• Experience with Pragmatic Marketing, Design Thinking, Jobs To Be Done, or Continuous Discovery, or equivalent
• Comfort building working prototypes or demos with AI app builders and coding copilots
• Experience in Agile development and familiarity with product and analytics tooling including Jira, Aha, and Amplitude