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Perk (formerly TravelPerk) is hiring its first Director of Go-to-Market Engineering to lead the technical infrastructure powering the revenue organization of 800+ people. You will own GTM Engineering end-to-end: architecture decisions, tooling strategy, team leadership, and hands-on building. You report to the VP of Revenue Operations and lead a small senior team across Europe and North America.
The role is split between strategic architecture and hands-on execution. On the strategy side, you'll define how Perk's CRM, enrichment stack, AI agents, and data layers fit together. You'll make tooling decisions (adopt, consolidate, retire), set the roadmap with revenue leadership, and establish engineering standards for the team. You'll own the full GTM automation stack: account prospecting (TAM sourcing, ICP/intent scoring, lead distribution), AE productivity (CRM autofill, quoting, meeting prep), and Account Management intelligence (risk signals, whitespace detection).
On the execution side, you'll design and build in Clay (tables, enrichment workflows, AI columns, webhooks, API integrations), own the orchestration layer that decides which records enter workflows and when, and build agentic workflows using modern LLMs to automate research, qualification, and data entry. You'll write production code in Python, SQL, SOQL, or TypeScript as needed.
You bridge commercial and technical worlds: translating revenue problems into technical architecture and technical output into measurable business impact. You'll quantify outcomes (e.g., time saved for quota-carrying roles) and communicate results to leadership. You lead and grow a small, senior team across two regions, setting clear ownership and review discipline to ship fast and safely.
Success requires deep GTM Engineering experience at scale in B2B SaaS, proven delivery of systems hundreds of sellers relied on (not pilots), and time as both builder and leader. You need production Clay expertise (complex tables, waterfall enrichment, webhooks, AI logic), deep Salesforce fluency (data model, integration patterns, constraints), working proficiency in at least one programming language, and architecture instincts for scale, monitoring, and recovery.
