TL;DR: We’re looking for a GTM Engineer to automate low-value commercial work and build the systems that generate qualified pipeline at scale. You’ll own the GTM infrastructure end to end: design the data model, keep the CRM reliable, connect the stack, deploy AI agents, automate outbound and inbound workflows, and continuously improve how we acquire and retain customers.
About White CircleWhite Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.
We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
We process over 100M+ API calls every month
We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model
We’re at a multi-million dollar run rate already having signed customers like Lovable and multiple neobanks. You’ll be joining at the most exciting time - early enough that the equity can be life changing but at a point where demand has been proven.
We’re a small, highly focused team. If you want to work deeply on hard problems and build the category-defining company in AI safety - this role is for you!
Automate low-value work out of the commercial process so the Sales team can spend more time closing deals
Design and build the systems that power how we find, acquire, and retain customers (both outbound and inbound)
Own the CRM: you make sure our data is clean, structured, and reliable
Build internal tools, API integrations, and custom automation logic
Have real ownership & shape the playbook: what we build, use, how it fits together, and how it scales
Design and deploy AI agents across the GTM motion (e.g., account research, pre-call intelligence, personalised outreach, etc)
Wire it directly into our operational systems so it changes how the team works
Design the GTM data model (accounts, contacts and opportunities)
Build and manage data pipeline, enrichment and integrations across the stack
Build, ship and iterate fast
6+ years of experience in GTM engineering, technical RevOps, or a growth role where you were building automations and pipelines
Experience designing and scaling systems in a high-growth company
Hands-on with modern GTM tooling - Claude Code, Clay, Apollo, Instantly, n8n or similar - you've built multi-step enrichment and sequencing workflows, not just set up a table
Comfortable with Python or SQL well enough to work with data, call APIs, and build lightweight scoring or enrichment logic
Top-of-funnel focused - you know how to build systems that generate qualified pipeline at scale, from ICP definition through to booked meetings
Experience in programmatic SEO and AEO
Analytical and experimental mindset: proven ability to design tests, measure impact, and iterate quickly.
Proven AI deployment experience (e.g., automations, agents, workflows)
In your first six months, we would expect you to identify the highest-converting early segments, build a functioning outbound and follow-up engine, create clear messaging for one or two strong wedges, generate a meaningful pipeline of qualified conversations, and help convert early pilots or customers. Just as importantly, we would expect the company to understand its GTM motion far better because of your work.
Compensation & benefitsCompetitive compensation, including equity
Flexible time off
An office in central London, with a flexible hybrid setup
Mental health support, including coverage for therapy when you need it
Lunch and dinner covered when you work from the office
Learning and development support for courses, conferences, and opportunities to grow your skills
All the hardware, subscriptions, tools, and services you need
Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella
Intro call with Talent (30 min)
Take-home assignment
Interview with Head of Revenue & Data Engineer (60 min)
Final call with CEO & Head of Engineering (45 min)
