Product Management Lead, AI
Job Summary
- Drive the agentic strategy:Drive the product vision roadmap and success metrics for agentic experiences across the portfolio from focused agent workflows to full orchestration.
- Build agentic experiences that ship:Design and deliver AI-native products (agents copilots human-in-the-loop workflows tool use retrieval and reasoning) that are reliable explainable and production grade.
- Make autonomy trustworthy:Treat governance as an enforced constraint not an aspiration. Define hard limits output verification reversibility escalation paths and auditability so users can trust what an agent does on their behalf.
- Drive product adoptionfor AI:Own activation onboarding and the path to habitual use. Reduce friction design for time to value and grow adoption across new customers existing customers and internal teams.
- Drive growth:Build and instrument growth loops expansion and retention. Partner with go-to-market and growth to turn capability into usage usage into value and value into revenue.
- 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.
- Run continuous discovery:Engage customers and prospects through interviews onsite visits workshops and discovery sessions. Map opportunities to solutions validate before building and keep a living view of unmet needs.
- Master the market:Develop deep expertise in DFIR the agentic AI landscape competitive dynamics and emerging model and tooling trends 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 and prototyping) and model AI-native ways of working that raise the bar for the wider product team.
- Travel:5-15%.
Agentic AI experience (required):You have built and shipped agentic or AI-native product experiences (agents copilots autonomous or semi-autonomous workflows) in production. You can speak concretely to what you shipped what worked and what did not.
AI-native operator (required):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.
Experience:7-10 years in product management ideally with enterprise SaaS including meaningful time on AI or ML-powered products.
Adoption and growth:Demonstrated track record driving product adoption activation retention and growth ideally in a product-led motion.
Data-driven decision making:Fluent with product analytics and experimentation. You instrument what you build and let metrics guide tradeoffs.
Product discovery:Skilled in continuous discovery and validation techniques (customer interviews opportunity-solution mapping Jobs To Be Done).
Technical acumen: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.
Analytical mindset:Skilled at interpreting market data customer insight and usage metrics to drive decisions.
Influence and communication:Strong collaboration skills and the ability to communicate effectively with both technical teams and executive stakeholders.
Ownership mindset:Act as the champion for your product anticipating challenges removing obstacles and driving momentum to meaningful business results.
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.
The Compensation range is for the primary location for which the job is posted. Please note that the actual compensation may vary depending on location and job-related factors such as qualifications experience knowledge and skills. If you are applying for this role outside of the primary location and you are selected for an interview the Talent Acquisition Partner can share more information with you.If the compensation structure for the role includes an incentivecomponent(i.e. most Sales roles) the range belowrepresentstotal target compensation (TTC) (base salary variable).
$175000 - $225000 (CDN) a year
$150000 - $200000 (USD) a year
Salary range (min - max)
Position Type:New Position
About Company
Unlock the truth. Protect the innocent. We provide organizations with innovative tools to investigate cyberattacks and digital crimes.