Who you are

- 5 to 8 years in B2B marketing, demand generation, marketing operations, or GTM systems, with a track record of improving measurable pipeline outcomes

- Thinks like an engineer: approaches demand gen as a system to be designed and optimized, not a campaign calendar to be managed

- Hands-on experience with AI tools in a real GTM context — inbound automation, outbound sequencing, intent signal processing, or similar — integrated into actual workflows, not just piloted

- Deeply data literate: can build attribution models, diagnose full-funnel performance, and identify root causes without needing a translator

- Fluent across the contemporary Demand stack: ABM platforms, marketing automation, CRM, intent data, AI orchestration tools. Understands how the components connect and where they break, and is hands-on enough to build and debug in these systems, not just navigate the UI

- Comfortable building, whether with no/low-code automation platforms or API integrations, enough to prototype and ship without waiting on engineering

- Strong cross-functional operator: drives change through influence across Demand Gen, Product Marketing, Campaign Management, and sales without direct authority

- Cybersecurity or enterprise tech background preferred but not required

What the job involves

- The Manager, Demand Engineering reports to the SVP, Growth Marketing, and operates as a cross-functional GTM architect embedded in the marketing organization, across Demand Generation, Product Marketing, and Campaign Management

- This is a builder role: equal parts operator and architect, with a mandate to ship working systems, not slideware

- This person’s mandate is to identify where the revenue funnel breaks or leaks, across the full funnel from top to bottom, and engineer solutions to fix them

- That includes top-of-funnel inbound and outbound automation, mid-funnel conversion friction, attribution gaps, and handoff failures between marketing and sales
- The fix is not more campaigns; it is redesigning the GTM motion itself: introducing AI-powered orchestration, building the data infrastructure needed to make the system visible, and establishing a new operating model for how BeyondTrust creates and converts demand

- This role connects Demand Generation, Product Marketing, and Campaign Management, using AI and GTM orchestration to make the whole system perform at a higher level





- This role drives systemic change across three marketing functions rather than owning a single defined area:

- Demand Generation is the team whose outcomes this role is designed to improve
- The role works alongside Demand Gen leadership to diagnose performance gaps, introduce AI-powered workflows, and fix programs that are structurally underperforming

- Product Marketing provides the messaging frameworks and competitive context the demand system must be grounded in

- This role feeds demand signals back to Product Marketing and ensures demand gen engineering decisions reflect current positioning

- Campaign Management handles execution
- This role works with Campaign Management to translate GTM Engineering decisions into programs, and to identify which execution patterns need to be redesigned at the system level

- Beyond marketing, this role will partner with internal teams, including Revenue Operations, where marketing systems intersect with CRM data and pipeline reporting

- Funnel Intelligence and Inefficiency Identification

- Analyze the full revenue funnel — top to bottom — to identify where pipeline is leaking, stalling, or failing to convert. This includes top-of-funnel inbound and outbound motion, mid-funnel conversion gaps, attribution blind spots, and marketing-to-sales handoff failures

- Translate funnel analysis into a prioritized engineering roadmap — interventions ranked by pipeline impact and feasibility, with baselines and improvement tracked over time

- Make funnel performance consistently visible and trusted by revenue leadership

- AI and Demand Gen Orchestration

- Design and implement AI-powered workflows across the full funnel: inbound lead qualification, outbound sequencing, intent signal processing, lead scoring, content personalization, and pipeline acceleration

- Evaluate and introduce demand orchestration platforms that connect data signals, marketing execution, and sales activation into a coordinated, automated motion





- Build internal playbooks so AI and automation become embedded in day-to-day demand operations, not one-off experiments, and stay ahead of the evolving tooling landscape

- Establish guardrails for safe, governed AI use against marketing and revenue data, including permissioning, read/write boundaries, and human-in-the-loop checkpoints, so automation earns trust as it scales

- GTM System Architecture
- Design and continuously optimize BeyondTrust’s demand engine — the integrated system of data signals, technology platforms, AI-powered workflows, and coordinated tactics that produces pipeline at scale

- Define the instrumentation and measurement framework that makes every component of the demand engine visible, attributed, and connected to revenue outcomes

- Engineer durable solutions to systemic misalignments between strategy, execution, and infrastructure, not incremental patches

- Translate ambiguous “we should automate this” ideas into scoped, measurable, and maintainable systems, with a bias toward solutions that are trustworthy over clever-but-fragile

- Cross-Functional GTM Alignment

- Serve as the connective layer across Demand Generation, Product Marketing, Campaign Management, and sales, translating insights from each into engineering decisions that improve the system as a whole

- Drive GTM planning cadences that create a shared view of funnel performance, pipeline gaps, and the prioritized GTM Engineering roadmap

- Build trust across functions by delivering insights and solutions that make each team more effective — driving change through influence, not org chart authority

- Data, Intelligence, and Attribution

- Build and maintain the attribution models, reporting frameworks, and data pipelines that make the demand engine measurable, accounting for multi-touch, multi-channel buyer journeys

- Use data to identify gaps by segment, region, and product line, and translate findings into engineering decisions

- Own the systems that keep marketing data clean and trustworthy, so downstream reporting and AI outputs are reliable by default and trusted across the revenue organization

- Product Marketing Collaboration
- Ensure the demand system is grounded in current product positioning and competitive context, and feed demand signals back to Product Marketing to inform strategy

- Align the Demand Gen Engineering roadmap with product launch timelines across all product lines

📌 Demand Engineering Manager (Canada)
🏢 BeyondTrust
📍 Canada