Staff Technical Lead - Marketing Studio Intelligence

About this role

<h3>Staff Technical Lead - <strong>Marketing Studio Intelligence</strong></h3> <h3>Location: UK - <a href="https://www.hubspot.com/careers/hybrid-work">Remote, Flex, or Office</a></h3> <p>Our mission at HubSpot is to help millions of organizations grow better.&nbsp;<strong>Marketing Studio Intelligence </strong>is building the intelligence layer behind HubSpot’s next-generation marketing platform. We bring together campaign performance, marketing assets, CRM data, and AI to help marketers understand what’s working, uncover opportunities, and discover what to do next.&nbsp;</p> <p>This is a deeply customer-focused space, where we work closely with marketers to understand real problems and turn rapidly evolving AI capabilities into simple, trustworthy experiences that deliver meaningful value.</p> <p>As a Staff Technical Lead, you’ll lead a small team of 2 - 3 engineers while staying deeply hands-on. You’ll partner closely with Product and UX to shape and build AI systems at scale, tackling ambitious problems across agentic systems, intelligent decisioning, AI quality, and evaluation.</p> <h3><strong>What You’ll Do</strong></h3> <ul> <li>Lead a small team of 2 engineers, setting technical direction and helping the team deliver against shared product and engineering goals.</li> <li>Design, build, and evolve backend services that power campaign integrations, measurement, automation, and intelligent capabilities across Marketing Studio.</li> <li>Stay hands on with development, contributing production quality Java code and working directly on the team’s most important technical challenges.</li> <li>Lead technical design for integrations between Marketing Studio, HubSpot campaign systems, marketing assets, CRM data, and other platform capabilities.</li> <li>Build scalable systems that support campaign performance reporting, attribution, analytics, and intelligent recommendations.</li> <li>Help shape backend capabilities for AI powered experiences that use campaign context, CRM data, and engagement history to generate insights and recommendations.</li> <li>Break complex initiatives into clear technical plans and help engineers navigate architecture decisions, dependencies, tradeoffs, and delivery risks.</li> <li>Coach and mentor engineers through design reviews, code reviews, feedback, and day to day technical guidance.</li> <li>Partner with Product and UX to shape priorities and translate customer problems into technical approaches that balance speed, quality, and long term system health.</li> <li>Drive alignment across engineering teams when work spans shared services, campaign infrastructure, data systems, integrations, or Studio platform capabilities.</li> </ul> <h3><strong>What You’ll Bring</strong></h3> <ul> <li>Significant experience designing, building, and operating backend software systems in production environments.</li> <li>Strong <strong>Java</strong> development skills and experience building production grade backend services, as well as Kafka, MySQL or comparable backend technologies.&nbsp;</li> <li>Experience technically leading a small engineering team while remaining an active contributor to the codebase.</li> <li>Experience coaching and mentoring engineers and helping others grow their technical skills and ownership.</li> <li>Strong understanding of system design, scalability, reliability, performance, fault tolerance, testing, and observability.</li> <li>Experience designing and delivering AI-powered products, agentic workflows, AI agents, recommendation systems, decisioning systems, personalization, or next-best-action experiences.</li> <li>Experience building the backend orchestration, services, APIs, and feedback loops that connect AI or ML models to real customer actions and outcomes.</li> <li>Experience working with complex, high-volume data and ensuring AI outputs are relevant, explainable, trustworthy, and useful to customers.</li> <li>Experience defining evaluation, monitoring, and learning mechanisms to assess the quality and impact of AI-generated recommendations or insights.</li> <li>Ability to partner effectively with ML and data science teams to integrate and productionize models, without necessarily owning model training or core ML infrastructure.</li> <li>Strong product judgment and customer empathy, with the ability to identify which insights will create genuine value and how they should be presented to customers.</li> <li>Ability to communicate complex AI concepts clearly and influence Product, Engineering, UX, Design, and business stakeholders.</li> </ul> <p><strong>Nice to Have Qualifications</strong></p> <ul> <li>Direct experience with recommendation systems, decisioning, personalization, ranking, experimentation, or next-best-action products.</li> <li>Experience integrating CRM, marketing, campaign, advertising, or customer data across multiple systems.</li> <li>Experience in marketing technology or other domains where products help customers make data-informed decisions.</li> <li>Experience with Python or another transferable backend language in addition to, or instead of, Java. Check out our<a href="https://product.hubspot.com/blog"> engineering blog</a> to learn more.</li> </ul> <p>Direct marketing or recommendation-system experience is a plus, but not required. We also welcome candidates with transferable experience building customer-facing AI products in areas such as customer support, prospecting, content, advertising, or other decision-support domains.</p> <p>&nbsp;</p><div class="content-conclusion"><hr> <p><em data-stringify-type="italic">We know the</em><em data-stringify-type="italic"> <a class="c-link" href="https://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/" target="_blank" data-stringify-link="https://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/" data-sk="tooltip_parent">confidence gap</a></em><em data-stringify-type="italic">&nbsp;and</em><em data-stringify-type="italic"><a class="c-li