Demand Generation · Growth Engineering
Shipsy is hiring a Growth Engineer to build the machine that finds, warms and converts enterprise logistics buyers. You will write the campaign and build the automation that runs it. You will ship the landing page and run the test that proves it works.
Shipsy is hiring a Growth Engineer to build the machine that finds, warms and converts enterprise logistics buyers. You will write the campaign and build the automation that runs it. You will ship the landing page and run the test that proves it works.
A bit about us. Shipsy builds AI-native logistics software for shippers, carriers and postal operators. We’re at roughly $27M ARR, growing about 45% a year, and Gartner has named us a Niche Player in the Gartner® Magic Quadrant™ for Transportation Management Systems. Our buyers are Heads of Transport, COOs and CIOs at multi-billion dollar companies. They get a lot of cold email and ignore nearly all of it. What gets through is a message that lands at the right moment, says something specific about their operation, and backs it up.
The role sits at an intersection of marketing, sales and engineering, and you’ll spend time with all three. Day to day you’ll work alongside the content, SEO and paid teams, and you’ll report directly into GTM leadership. You’d be based in India, with good overlap to work with colleagues and customers in Europe and the Middle East.
There are five areas. The goal in each is the same: build something that keeps running when you’re not looking at it.
AI first, by default. Your first move on any task is to ask how an agent or workflow could do it. You use Claude every day to research accounts, draft copy, write code and analyse data. You build agents and n8n workflows that do the repetitive work, and you document them so others can reuse them.
Builder who ships. You ship the thing yourself. If a landing page needs a form, you wire it. If a list needs enrichment, you write the script. You call engineering when a problem needs engineering, and you arrive with a spec.
High agency. Nobody will hand you a playbook. You will get a goal (pipeline from a segment, visibility in AI search, cost per meeting) and decide how to hit it. When something blocks you, you find a way around it or escalate the same day.
Comfort with ambiguity. Priorities shift with deals, markets and quarters. You make a call with 70% of the information, state your assumption, and adjust when the data comes in.
Bias to measurement. Every experiment starts with a hypothesis and a success metric. You kill what does not work in weeks and share what you learned.
You have 3 to 6 years in growth, demand gen, marketing ops or a technical marketing role, and you can point to systems you built that produced pipeline.
| Area | Tools you will use |
|---|---|
| AI and agents | Claude, Claude Code, MCP connectors, custom agents |
| Automation | n8n, webhooks, APIs, Python scripts |
| Data and enrichment | Clay, Apollo, ZoomInfo, waterfall enrichment, scrapers |
| Outbound | Sequencing tools, dedicated sending domains, deliverability monitors |
| CRM and analytics | HubSpot, GA4, Search Console, BI dashboards |
| Paid and social | LinkedIn Campaign Manager, Google Ads |
| Web and SEO | CMS, Vercel, Semrush, Ahrefs, AI search visibility trackers |
Your first 90 days end with three systems live and measured.
We judge what you build. The process runs in four steps over two to three weeks.
To apply, send your CV and a link to something you built: a workflow, an agent, a dashboard or a campaign with results.
Show your interest
A handful of questions, no résumé upload required. We review every submission personally and respond within 5 working days.
Other senior roles
Own an entire region’s go-to-market, from the target account list and displacement strategy through to the pipeline number.
Read the role →Build the platform that plans, dispatches and settles millions of shipments a day.
Read the role →Own a core slice of the platform end to end, from the customer problem down to the shipped feature.
Read the role →Logistics is too critical for reactive systems. The world’s leading enterprises are amplifying their teams with AI that acts, so their people can focus on what matters most.