Staff Technical Lead - Marketing Studio Intelligence
HubSpot Care Score 46
Remote - United Kingdom · Remote · Engineering · Posted 2026-08-26
16w paid maternity · 16w paid paternity · IVF coverage · Fertility support
About this role
Staff Technical Lead - Marketing Studio Intelligence Location: UK - Remote, Flex, or Office Our mission at HubSpot is to help millions of organizations grow better. Marketing Studio Intelligence 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. 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. 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. What You’ll Do Lead a small team of 2 engineers, setting technical direction and helping the team deliver against shared product and engineering goals. Design, build, and evolve backend services that power campaign integrations, measurement, automation, and intelligent capabilities across Marketing Studio. Stay hands on with development, contributing production quality Java code and working directly on the team’s most important technical challenges. Lead technical design for integrations between Marketing Studio, HubSpot campaign systems, marketing assets, CRM data, and other platform capabilities. Build scalable systems that support campaign performance reporting, attribution, analytics, and intelligent recommendations. Help shape backend capabilities for AI powered experiences that use campaign context, CRM data, and engagement history to generate insights and recommendations. Break complex initiatives into clear technical plans and help engineers navigate architecture decisions, dependencies, tradeoffs, and delivery risks. Coach and mentor engineers through design reviews, code reviews, feedback, and day to day technical guidance. Partner with Product and UX to shape priorities and translate customer problems into technical approaches that balance speed, quality, and long term system health. Drive alignment across engineering teams when work spans shared services, campaign infrastructure, data systems, integrations, or Studio platform capabilities. What You’ll Bring Significant experience designing, building, and operating backend software systems in production environments. Strong Java development skills and experience building production grade backend services, as well as Kafka, MySQL or comparable backend technologies. Experience technically leading a small engineering team while remaining an active contributor to the codebase. Experience coaching and mentoring engineers and helping others grow their technical skills and ownership. Strong understanding of system design, scalability, reliability, performance, fault tolerance, testing, and observability. Experience designing and delivering AI-powered products, agentic workflows, AI agents, recommendation systems, decisioning systems, personalization, or next-best-action experiences. Experience building the backend orchestration, services, APIs, and feedback loops that connect AI or ML models to real customer actions and outcomes. Experience working with complex, high-volume data and ensuring AI outputs are relevant, explainable, trustworthy, and useful to customers. Experience defining evaluation, monitoring, and learning mechanisms to assess the quality and impact of AI-generated recommendations or insights. Ability to partner effectively with ML and data science teams to integrate and productionize models, without necessarily owning model training or core ML infrastructure. 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. Ability to communicate complex AI concepts clearly and influence Product, Engineering, UX, Design, and business stakeholders. Nice to Have Qualifications Direct experience with recommendation systems, decisioning, personalization, ranking, experimentation, or next-best-action products. Experience integrating CRM, marketing, campaign, advertising, or customer data across multiple systems. Experience in marketing technology or other domains where products help customers make data-informed decisions. Experience with Python or another transferable backend language in addition to, or instead of, Java. Check out our engineering blog to learn more. 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. We know the confidence gap and impostor syndrome can get in the…