GTM Engineer

Job Description

Basware is the clear market leader in Invoice Lifecycle Management, trusted by over 6,000 global customers and recognized #1 by Gartner, Forrester, and IDC. We revolutionized how the world’s largest organizations manage and automate AP, processing more than $10 trillion in invoices with unmatched accuracy, compliance, and control. If you’re inspired by innovation, growth, and a value‑driven culture, this is your chance to help shape the future of finance.

Basware's Marketing Operations team builds the technical backbone behind our go-to-market motion, across inbound, outbound, and retention and expansion. That means systems integration, data orchestration, and AI-assisted workflows across the marketing and sales stack.

The GTM Engineer designs and builds the automations, integrations, and AI agents that let marketing scale output without adding headcount. That includes the traditional GTM engineering work, like lead orchestration, routing, and scoring, but it also extends into agentic support for campaign creation, ABM personalization at scale, and project and database management across the wider marketing organization.

The role is positioned for a global B2B SaaS environment and should bring enough experience to independently assess tradeoffs across speed, scale, data quality, privacy, AI governance, adoption, and commercial impact.

This is a hands-on technical role. It partners closely with Marketing Operations, Growth Marketing, Customer Growth Marketing, and Marketing Strategy. The GTM Engineer is the go-to technical voice on what's scalable and sound, turning strategy into working systems other marketers can actually use. The role remains hands-on, but is expected to operate with senior-level ownership of GTM engineering priorities, technical decision-making, stakeholder influence, and scalable delivery across Marketing and Revenue teams. It partners closely with Marketing Operations, Growth Marketing, Customer Growth Marketing, Marketing Strategy, Sales, RevOps, and IT to turn GTM strategy into reliable systems other marketers can actually use.

Key responsibilities

1) GTM Systems Architecture & Integration

Design, build, and maintain automations and integrations across the marketing and sales stack, including Salesforce, HubSpot, Asana, Clay, intent/ABM tooling, attribution platforms, and AI-SDR tools. Own the technical integration points and roadmap so data and handoffs between systems stay reliable, scalable, auditable and low-maintenance across global GTM teams.

2) AI-Assisted Campaign Creation

Build agentic workflows that support campaign creation end to end, from brief intake to first-draft asset generation, using Claude Enterprise, Copilot Studio, and comparable tools. Orchestrate agents across MCP connectors to optimize AI usage across the tech stack. Partner with Growth Marketing and Customer Growth Marketing to cut manual production time on recurring campaign types, while keeping human review in the loop.

3) ABM Personalization at Scale

Design and build workflows that generate personalized, on-brand ABM content and outreach at scale, drawing on firmographic, intent, product usage, and customer health data. Keep personalization logic aligned with the ILM Messaging Framework and brand guidelines, and build in review checkpoints so output stays accurate and on-brand.

4) Asana Project & Database Enrichment

Build and maintain automations that keep Asana project and database structures clean and synced with the broader GTM stack. This reduces manual upkeep for campaign, content, and operations teams and gives marketing leadership accurate, real-time visibility into work in flight.

5) Cross-System Data Flow & Reporting Infrastructure

Ensure GTM systems feed clean, structured and enriched data into systems and reporting and analytics tools, supporting accurate measurement of pipeline, campaign, and content performance.

6) Governance, Experimentation & Iteration

Flag design or scale risk in workflows and agents before they ship, operating within the existing AI review layer and AI Innovation Board governance. Run technical experiments on automation and agent logic, and iterate based on performance data and commercial impact in partnership with GTM and marketing leadership.