[Hiring] Staff Technical Lead @HubSpot

Role Description

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.

• 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.

Qualifications

• 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.
• 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.