обновлено 59 минут назад
Principal Software Engineer (AI Trust & Safety)
261 000 - 353 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Software Engineer (AI Trust & Safety) (Java, ML): Designing and implementing scalable Trust & Safety services and decisioning systems that protect access, identity, products, and customer journeys with an accent on AI-driven risk detection, secure cloud-native architecture, and regulatory controls. Focus on integrating ML and LLM capabilities into production workflows, building resilient high-availability systems, and leading architecture across multiple engineering teams.
Location: New York, New York, United States
Salary: $261,000–$353,000 annual base pay, plus cash bonus, equity rewards, and benefits
Company
is a financial technology platform whose products include TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Define Trust & Safety architecture across access, identity, product misuse, risk, and compliance use cases.
- Design and implement Java-based core services and decisioning components using Spring, microservices, event-driven architectures, and cloud-native platforms.
- Integrate machine learning models into production workflows for risk scoring, classification, anomaly detection, and prioritization.
- Apply AI and LLM-based tools to automate triage and classification of risk-related events and content.
- Improve reliability, performance, observability, SLOs, alerting, runbooks, and on-call readiness for safety-critical systems.
- Lead architecture discussions, influence cross-team roadmaps, mentor engineers, and guide prototypes into production-ready solutions.
Requirements
- 10+ years of experience designing and building large-scale distributed backend systems in production.
- Extensive hands-on experience with Java, JVM, Spring/Spring Boot, microservices, asynchronous processing, and event-driven architectures.
- Experience in risk, security, safety, identity, access, financial or transactional flows, content integrity, or compliance systems.
- Experience with cloud-native services on AWS, GCP, or equivalent, including containers, Kubernetes, managed data stores, and Kafka or Kinesis.
- Experience integrating and operating ML models in production, plus familiarity with modern AI and LLM tooling.
- Strong knowledge of API design, performance, concurrency, resiliency, observability, secure coding, authentication, authorization, privacy, and data protection; BS/MS in a relevant technical field or equivalent experience.
Nice to have
- Experience working in globally distributed, matrixed organizations and ambiguous problem spaces.
- Experience influencing architecture across multiple teams and mentoring engineers in system design and operational excellence.
Culture & Benefits
- Cross-functional collaboration with Product, Data Science, Security, Compliance, Risk, Operations, and platform teams.
- Globally distributed working environment with an emphasis on secure-by-design, privacy-by-design, and sustainable solutions.
- Competitive compensation with performance-based cash bonuses, equity rewards, and benefits.
- Regular pay comparisons across ethnicity and gender categories to support fair compensation.
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