• Join a high-trust engineering team of 4 Fullstack Engineers. • Build, deploy (GitHub Actions), and monitor features. • Evolve Go-based backend and Terraform infra.

• As a GTM Engineer you are the technical backbone of our go-to-market: you build systems, automations and data flows that make Sales & Marketing faster, cleaner and scalable. • You think in funnels, data and workflows — and implement them so that pipeline is predictable and revenue teams can work efficiently. • GTM Systems Architecture: you analyze our entire revenue funnel (Lead → MQL → SQL → Demo → Close) and build a robust system landscape including ownership, field logic and process gates in HubSpot (or equivalent). • Lifecycle & Funnel Automation: you implement automations for routing, enrichment, sequences, follow-ups, reminders, deal stages, tasks, SLAs and nurture tracks. • AI in GTM Processes: you integrate LLMs (e.g., OpenAI API, Claude) for use cases such as lead scoring, meeting prep, call summaries, email drafts, persona/ICP insights, objection handling, content repackaging and research — with clear guardrails, quality checks and logging. • Tooling & Data Connectivity: you connect our tools (CRM, Notion, Slack, Google Workspace, calendars, forms, enrichment tools etc.) via webhooks/APIs so data flows automatically and GTM processes run "always-on". • Tracking, Attribution & Reporting: you ensure we have reliable funnel data: clean source logic, campaign/UTM standards, lead and deal attribution, and dashboards for pipeline, conversion, CAC/payback signals (depending on maturity). • Experimentation Engine: you build infrastructure to quickly test growth experiments (messaging, channels, targeting, sequencing) — including measurability, documentation and learnings. • Enablement & Documentation: you document systems, build playbooks and train Sales/Marketing so processes remain stable even without you.

• Identify, define and document data assets • Build scalable data pipelines and migrate data into the Enterprise Data Management (EDM) environment • Develop and maintain data products and pipelines • Implement data management practices leveraging commercial tools • Partner with Solution Architects to design and implement processes for the evolving EDM environment • Create detailed, well-structured data models and relationship diagrams • Conduct business process analysis • Ensure data quality, integrity and timeliness by developing robust and resilient data pipelines • Integrate structured and unstructured data sources into the Lakehouse architecture • Provide technical leadership and mentorship across teams

• Building and enhancing modern React applications • Translating UX designs into scalable, production-ready components • Developing and maintaining backend APIs (Node.js and/or Python) • Deploying and maintaining services in AWS (serverless architecture) • Owning features end-to-end (development → deployment → monitoring) • Contributing to architectural discussions and platform scalability • Ensuring performance, reliability, and observability in production