About the Role
You build and optimize risk detection and mitigation systems that protect users in real time at scale You collaborate with Data Science ML Risk Analysts Product and Compliance teams to implement proactive and reactive controls You mentor engineers conduct rigorous code reviews and champion engineering best practices You own system quality and drive incident response and post mortems to ensure reliability
Requirements
- 5+ years of backend software engineering experience with a track record of delivering complex high impact systems in production environments
- Deep proficiency in backend languages (Go Ruby Python or Java) with demonstrated experience designing distributed systems including microservices event driven architectures and REST GraphQL APIs
- Proven ability to translate ambiguous requirements into clear technical plans and working architectures driving technical clarity across engineering product and data science teams
- Track record leading end to end projects with long term impact including scoping design implementation monitoring and mentoring other engineers through the process
- Experience leading incident response conducting post mortems and driving measurable operational improvements in high availability systems
- Utilizes generative AI responsibly maintaining human oversight to deliver business ready outputs and drive measurable improvements in workflow efficiency cost and quality
Responsibilities
- Lead the design and delivery of complex risk platform features end to end from architecture through implementation deployment and monitoring with stringent requirements for correctness performance and reliability
- Drive architectural decisions that shape risk detection and mitigation systems translating ambiguous business requirements into scalable architectures that balance fraud prevention with user experience
- Partner cross functionally with Data Science ML Risk Analysts Product and Compliance teams to build proactive systems (real time decisioning engines model driven fraud detection) and reactive solutions (incident response tooling compliance driven risk controls)
- Build AI native risk systems that leverage fleets of agents to automate complex detection and response workflows significantly reducing the need for manual intervention
- Strengthen the team by mentoring engineers conducting rigorous code reviews writing technical design documents for complex systems and championing engineering best practices across the codebase
- Own system quality and operational excellence by proactively addressing technical debt driving bug triaging and leading incident response and post mortems to ensure platform reliability
Benefits
- Equity
- Bonus eligibility
- Medical insurance
- Dental insurance
- Vision insurance