Staff Product Engineer, AI
IntercomBerlin, GermanyPosted 7 April 2026
Job Description
Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences.
Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.
Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.
Speed is something we fight for every day at Intercom, and we believe Berlin is built for people who share that instinct. We are drawn to Berlin by its rare blend of deep technical talent and rich creative culture – all within a vibrant, globally connected city that’s close to our RD hubs in Dublin and London. It’s a place where the best of the best technical talent thrive, and where people from around the world are eager to relocate and build ambitious products.
Our ambition is to hire 100 people in Berlin over the year ahead across engineering, AI, data science, product, and design. We believe this is the most exciting time to join, be the founding RD talent in the region and make a lasting impact as we build the world's number one customer agent!
What's the opportunity?
We’re looking for Staff Product Engineers to join the AI Group to build Intercom’s AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack.
Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.
We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.
We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.
If you are an experienced product engineer who takes an analytical approach to development and has some hands-on experience with ML systems, we'd love to hear from you!
What will I be doing?
Product Engineers in the AI Group
Build the systems that power Intercom’s flagship AI products. This usually means working in our ML Python tech stack, but at times also means working across the product on our Rails app too.
Work alongside our ML Scientists bring proof-of-concept code to production; ensuring it’s robust and scalable for real-world use.
Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers..
Contribute to all phases of software development including ideation, prototyping, and implementation and testing.
Play an active role in the hiring, mentoring, and career development of other engineers.
Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Intercom.
Profile we’re looking for
These are meant to be indicative, not hard requirements.
7+ years of experience shipping high-quality products.
No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team.
You can demonstrate significant impact in the wor ... (truncated, view full listing at source)
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