Backend / API Engineer, Radar
Stripe · Toronto · 8525 Radar - Eng · listed October 20, 2026
The shape of it
Seniority
Mid level
Experience asked
2+ years
Where
Not stated
Requirements listed
6
Length
617 words
In the posting’s own words
Radar helps businesses prevent payments fraud and abuse while enabling legitimate customers to transact with confidence. We combine machine learning and AI with the intelligence of Stripe’s global network to make sophisticated fraud prevention accessible to businesses of all sizes.
What it asks for · 6
- 2+ years of industry software engineering experience
- Strong coding skills in any programming language, with experience building and maintaining production software
- Ability to work across systems and technologies, learn unfamiliar codebases, and make thoughtful technical trade-offs
- A rigorous approach to problem solving, including using data to investigate issues and evaluate whether a solution works
- Strong collaboration and communication skills, with the ability to work across disciplines and contribute to your peers’ success
- An ownership mindset and comfort navigating ambiguity, taking initiative, and following through on user problems
Also a plus
- Experience building distributed systems or real-time services with demanding reliability and latency requirements
- Experience building APIs, developer platforms, or intuitive user interfaces for complex workflows
- Experience bringing ML or AI capabilities into production software
- Experience working on fraud prevention, abuse prevention, risk, or security
- Experience taking a product from an early idea to launch and iterating directly with customers
What the job covers
- Build and operate reliable, low-latency services that detect and prevent fraud and abuse at scale
- Design APIs and dashboard experiences that help businesses investigate threats, configure defenses, and understand how Radar protects them
- Develop the shared platform and infrastructure that enable teams to build and launch new Radar capabilities
- Work directly with users to understand emerging threats and turn those insights into broadly useful products
- Partner with ML engineers and data scientists to bring new signals, models, and AI capabilities into production
- Own projects end to end, from technical design and implementation through rollout, measurement, and iteration
- Uphold a high bar for engineering quality, reliability, and product craft while moving quickly as threats evolve
Tools and skills named
Models & research
- Machine learning5×
Cloud & infra
- Distributed systems
Security & compliance
- Security
Words the posting leans on
- experience9×
- fraud7×
- products7×
- users7×
- build6×
- abuse5×
- businesses5×
- capabilities5×
- payments5×
- radar5×
- requirements5×
- apis4×
- customers4×
- prevention4×
- production4×
- software4×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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