Staff Software Engineer

Customer Journey Engage Group

At HubSpot, we’re on a mission to help millions of organisations grow better. Our platform helps businesses manage their marketing, sales, service, and operations. Under the hood, our product is built to be flexible, secure, and empowering for both our customers and our engineering teams. We believe in autonomy, curiosity, and building a workplace where everyone can thrive. With our hybrid work model, you can work remotely anywhere in the UK or Ireland, or collaborate in-office in London or Dublin.

Meet the Teams in the Customer Journey Engage Group

Air Traffic Control owns the decision layer of the Unified Engagement Platform. The team builds the systems that determine which in-app nudges customers see, when they see them, and why. Their mission is to help users reach their goals through timely, contextual, data-driven engagement. As the platform evolves into a more scalable orchestration engine, the team is solving complex challenges around decisioning, experimentation, and cross‑product coordination.

Everboarding Engine is HubSpot’s platform for helping customers continuously unlock more value from our product. Using behavioural signals and rich context, the system recommends meaningful next steps beyond initial onboarding. It underpins key product experiences across HubSpot and requires strong architectural foundations to ensure reliability, scalability, and extensibility across hundreds of teams.

Customer Journey Engage sits at the intersection of product growth, intelligent personalisation, and lifecycle engagement. The systems you build will shape how millions of users experience HubSpot every day and directly influence retention, expansion, and long-term customer value.

In This Role, You Will

Set Technical Direction

• Define and evolve the architecture of our engagement and orchestration systems
• Lead the design of scalable, reliable, event-driven systems that power real-time decisioning
• Identify long-term technical investments that unlock product and business growth

Deliver High-Impact Solutions

• Write and ship production code with measurable user and revenue impact
• Lead cross-team initiatives that span multiple product groups
• Solve exceptionally complex technical problems that are broad in scope or deep in complexity

Influence Beyond Your Team

• Partner closely with Product, Data Science, Research, and GTM stakeholders
• Mentor engineers and elevate engineering standards across the group
• Push best practices that improve the broader HubSpot ecosystem

This is a hands-on technical leadership role. We are looking for someone who stays close to the code while guiding architectural and product direction.

Who You Are

We care less about specific tech stacks and more about engineering depth, judgment, and impact. You might be a great fit if you:

• Have extensive backend experience designing distributed systems at scale
• Are comfortable working with technologies such as Java, MySQL, AWS, Kafka, Kubernetes, or similar
• Are deeply user-focused and empathetic, understanding the challenges our customers face and how they move through our product
• Are excited about leveraging AI and data science in real-world, practical applications
• Have led high-value, cross-team initiatives with meaningful business impact
• Thrive in ambiguous problem spaces and can drive clarity across stakeholders
• Have demonstrated the ability to solve complex technical problems while weighing tradeoffs, with a deep understanding of developer experience and business needs
• Regularly mentor engineers and scale your technical influence
• Proactively shape the roadmap, surfacing opportunities and making clear trade‑offs instead of waiting for direction.
• Define and instrument clear success metrics for your work, and regularly use them to decide whether to double down, iterate, or pivot.
• Own problems end to end – you don’t wait for perfectly shaped work, you seek out the most important problems and drive them to resolution.
• (Nice to have) Have practical experience with ML‑powered systems in production (e.g., recommendation, ranking, or decisioning), working closely with data science/ML partners to ship, evaluate, and iterate on models.