Inside the Team Hiring Senior AI Engineers
What does a typical week look like for a Senior AI Engineer on your team?
Matteo: Your day usually starts with a standup with your squad to quickly sync on progress, raise blockers, and surface concerns. Most days, the remaining time is spent working on your tasks, collaborating with colleagues, and discussing solutions, issues, designs, and ideas.
What makes you immediately think, “This is the person”? And what’s the most common reason someone strong on paper doesn’t make it through?
Matteo: When I see energy, enthusiasm, strong ownership, and, of course, strong engineering knowledge. First-principles thinking and a solid understanding of engineering fundamentals are key - and often missing. There are also a few common red flags that reveal a shallow understanding of the field:
- not asking good clarifying questions when presented with a design problem
- jumping into solutioning too quickly
- mentioning tools before identifying the underlying problem and the right patterns to solve it
- talking about ML algorithms before setting up the evaluation framework
What would the first 90 days look like for a new hire - what would they work on, and who would they work with?
Matteo: The first week is mostly about onboarding: getting to know your colleagues, going through the company onboarding process, and learning everything you need to get started.
In the following weeks - let’s say the first 30 days - you’ll begin working on different tasks and projects with the support of a dedicated buddy, alongside the rest of your colleagues. We expect you to be excited, ramp up quickly, and feel motivated to contribute.
Within 90 days, you should be fully onboarded and operating as a fully functional member of the group, able to shape our products by bringing your unique skills to the table. You’ll be supported throughout, and your manager will work with you to help close any gaps that come up along the way.
Why do you stay at SmartRecruiters - and what specifically about your team or the work would make someone from the outside think, “I want to be part of that”?
Matteo: I’ve been at SmartRecruiters for almost five years - the longest tenure in my 16-year career.
I stay because I have plenty of space to design and build very innovative products, together with amazing, dedicated people who are trying to define what the future of hiring technology looks like.
What does “strong in AI/ML” actually mean for your team? Must-have vs. nice-to-have.
Matteo:
Must-have
- strong analytical thinking and the ability to break down new, unfamiliar problems effectively
- strong experience building evaluation frameworks, especially in NLP projects
- strong engineering fundamentals, clean coding, and strong software testing skills
- experience operating, debugging, and maintaining services in large distributed systems at scale
- experience designing and maintaining end-to-end ML pipelines, from data ingestion to deployment
- experience building LLM-driven agents and applications
- excitement for new challenges and comfort working in a roughly defined scope
Nice-to-have
- experience with our specific tech stack, including LangGraph, Langfuse, AWS, and Kubernetes
- experience with chatbots or conversational AI
What work background does the ideal candidate have?
Matteo: A mix of machine learning and software engineering, with strong experience in building and operating REST services in large distributed systems at scale.
What’s the most exciting thing coming in the next 6-12 months that a new engineer would walk straight into?
Matteo: We’re building a highly intelligent system that will make recruiters far more effective and efficient.
That means applying bleeding-edge technologies and techniques in the fast-moving field of LLM agents to build a product that no one in the industry has yet built successfully.
***
Interested in applying? You can explore the role here: Poland, Germany, and the United Kingdom.
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