GTM Engineer

Blackwall is an AI-enabled cybersecurity and web infrastructure company building the next generation of web traffic management technology. Following our recent $100 million Series C funding round at a $2.2 billion valuation, we're accelerating our global expansion and developing technology that transforms how internet traffic is managed and secured. Our flagship product, Gate Keeper, protects over 2.3 million websites and applications through more than 100 hosting and service partners worldwide.

As AI agents and automated systems reshape the internet, we're building the infrastructure to manage this increasingly complex environment. We're looking for an experienced and technically curious GTM Engineer to design, build, and continuously improve Blackwall's outbound growth engine. This isn't a traditional sales support or marketing operations position. We're looking for someone who can combine data science, AI, automation, and commercial understanding to build intelligent systems that determine who we should contact, when to reach them, how to personalise the message, and how to learn from the results.

You'll work at the intersection of engineering, data, and go-to-market strategy, taking ownership of the systems that power our outbound activities. We're particularly interested in people who enjoy building things, experimenting with new technologies, and turning complex problems into scalable, automated solutions.

• Build intelligent targeting systems:
  Develop and maintain dynamic Ideal Customer Profiles (ICPs), account segmentation, and propensity-to-buy models using CRM, firmographic, and engagement data.
• Apply data science to commercial challenges:
  Use Python, SQL, and predictive modelling to identify high-potential accounts, detect buying signals, and make actionable insights available in Hub Spot.
• Develop AI-powered research and enrichment workflows:
  Leverage LLMs, agents, Clay, and other automation tools to research companies, enrich data, and identify relevant prospects at scale.
• Personalise outbound engagement:
  Design AI-assisted messaging workflows that adapt to customer segments, roles, and buying triggers.
• Orchestrate multichannel outreach:
  Build and optimise outbound sequences across email, Linked In, and event invitations, continuously testing what works.
• Own Hub Spot automation and data infrastructure:
  Design and maintain CRM workflows, properties, integrations, and enrichment pipelines while ensuring data accuracy and consistency.
• Measure and optimise performance:
  Build reporting and feedback loops using Hub Spot and Jira, tracking outbound effectiveness, speed, process discipline, and lead quality.
• Build scalable processes:
  Document workflows, experiments, and successful approaches to create repeatable systems that can be maintained and improved by others.

• Strong experience building production-ready AI solutions, including LLM workflows, agents, prompt engineering, evaluation, and guardrails.
• Hands-on data science experience, particularly predictive modelling, propensity-to-buy scoring, feature engineering, and model validation.
• Proficiency in Python and SQL, with the ability to work independently with complex datasets.
• Deep understanding of Hub Spot, including workflows, properties, sequences, reporting, integrations, and CRM data architecture.
• Practical experience with Clay or comparable enrichment and automation platforms.
• Experience designing and implementing scalable automation systems, ideally in a B2B go-to-market environment.
• Strong analytical thinking and the ability to translate technical findings into actionable business recommendations.
• An experimental mindset, strong ownership, and the ability to build solutions rather than simply operate…