GTM Engineer

GTM Engineer

Full-Time 45000 - 55000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build innovative tech systems to connect Physical AI companies with investors and enterprises.
  • Company: Join a pioneering B2B media and events company in the exciting Physical AI market.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic startup environment with a chance to make a real impact.
  • Why this job: Be at the forefront of Physical AI and shape the future of technology.
  • Qualifications: Experience in GTM engineering, automation, and familiarity with tools like HubSpot and APIs.

The predicted salary is between 45000 - 55000 £ per year.

1VC is building a new B2B media and events company around one of the most important emerging technology markets: Physical AI.

Our ambition is to build the network that connects the companies developing Physical AI with the investors backing them and the enterprises deploying it.

We are looking for a GTM Engineer to help us build the technology and intelligence infrastructure behind that growth.

This is not a traditional marketing operations or sales operations role. You will work directly with the founder and our growing team to use AI, data and automation to identify the right companies and people, understand what matters to them, and create systems that allow us to engage thousands of highly relevant organisations without turning our outreach into mass marketing.

What you will build

You will help create a living map of the Physical AI ecosystem across robotics, embodied AI, autonomous systems, semiconductors, compute, sensors, edge AI and enterprise automation. That means building systems that can identify and track:

  • Physical AI founders and technology companies
  • Enterprise automation buyers
  • VCs and strategic investors
  • Technology partners
  • Potential speakers and contributors
  • Sponsors and exhibitors
  • Emerging companies, funding rounds and market signals

You will then turn that intelligence into practical GTM infrastructure.

What you will do

  • Build automated workflows for company and contact discovery, enrichment and segmentation.
  • Connect and improve our CRM, outbound, data and marketing systems.
  • Use AI agents and LLMs for account research, qualification, personalisation and market intelligence.
  • Develop sophisticated outbound workflows that combine automation with highly personalised human engagement.
  • Build lead scoring and prioritisation models so the team knows which organisations and individuals matter most.
  • Identify signals such as funding, hiring, product launches, partnerships and enterprise Physical AI initiatives.
  • Automate repetitive research and administrative work currently performed manually by the team.
  • Build dashboards that show us what is happening across our ecosystem and GTM activity.
  • Experiment constantly with new AI tools and approaches and deploy the ones that actually improve performance.
  • Ultimately, help us build a proprietary intelligence layer around the global Physical AI ecosystem.

What we are looking for

You are a builder. You see a repetitive process and immediately start thinking about how data, APIs, automation or AI could make it better. You will probably have experience across some combination of:

  • GTM engineering
  • Growth engineering
  • Revenue operations
  • Marketing technology
  • Data engineering
  • AI automation
  • Growth operations

You should be comfortable working with tools such as HubSpot, Clay, Instantly, Attio, n8n, Make and similar platforms. Experience working with APIs, webhooks, SQL and some Python or JavaScript would be highly valuable. More important than knowing every tool is being able to figure things out quickly.

You will probably love this role if...

  • You spend too much time experimenting with new AI tools.
  • You would rather build an automated workflow than repeat the same task 100 times.
  • You are fascinated by how companies grow.
  • You enjoy technology but also understand people.
  • You like working in environments where there isn’t already a playbook.
  • And you want to get involved early in building something.

Why 11VC?

Physical AI is moving rapidly from research labs into the real economy. Robotics, autonomous machines, embodied AI and intelligent infrastructure are beginning to reshape manufacturing, logistics, mobility, construction and many other industries. The ecosystem around those technologies is still being formed. We think there is an opportunity to build the media, intelligence and events platform that sits at the centre of it. You would join at the beginning and help build the infrastructure that allows us to scale it.

GTM Engineer employer: 11VC

At 11VC, we pride ourselves on being an innovative employer that fosters a dynamic work culture where creativity and experimentation are encouraged. As a GTM Engineer, you will have the unique opportunity to shape the future of the Physical AI ecosystem while working alongside passionate individuals in a collaborative environment. We offer competitive benefits, continuous learning opportunities, and the chance to be at the forefront of a rapidly evolving industry, making your contributions truly impactful.

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Contact Details:

11VC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land GTM Engineer

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We think you need these skills to ace GTM Engineer

GTM Engineering
Growth Engineering
Revenue Operations
Marketing Technology
Data Engineering
AI Automation
Growth Operations

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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How to prepare for a job interview at 11VC

Brush Up on Your Statistics

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Get Comfortable with Python and R

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