Staff Full Stack Software Engineer, Fraud Risk Platform
Palo Alto, CA or San Francisco, CA
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TripActions
Streamline your corporate travel management and expense processes in one app. Save time, gain efficiency, and reduce costs with this powerful, all-in-one solution.Navan is seeking a Staff Full Stack Software Engineer to join our Fraud Strategy team and help build a scalable, extensible risk platform to mitigate fraud across our Travel business. This engineer will be embedded within the business unit and will partner directly with data scientists and fraud strategy leads to create robust, real-time fraud mitigation solutions that protect both Navan and its customers.
You will lead the design and development of risk-centric services spanning onboarding, booking, and post-booking activities such as chargebacks and dispute management. Your work will power real-time decision engines, including third-party vendor integrations, feedback loops into machine learning models, and manual review tools that close the fraud detection and prevention lifecycle.
This hands-on role requires strong technical depth, the ability to operate independently, and a collaborative mindset to translate business needs into high-reliability applications running at scale in the cloud.
What You’ll Do:
- Architect and build extensible and scalable microservices to support real-time fraud detection and mitigation across the onboarding and booking flows for the travel customers.
- Work closely with Fraud Strategy Data Scientists to identify data needs, enabling real-time data ingestion and transformation of real-time and offline signals into the risk engine.
- Stand up and maintain a case management system to support manual decisioning and integrate outcomes back into model training pipelines.
- Develop integrations with third-party fraud vendors, ensuring their signals are correctly ingested and processed in the risk platform.
- Build observability dashboards to monitor performance, risk coverage, and system reliability.
- Own end-to-end CI/CD pipelines, including production deployment and best practices for release management.
- Ensure high reliability and performance in a cloud-native environment (AWS or similar).
- Serve as the engineering point person inside the business unit and help align risk mitigation engineering efforts with the broader product and engineering organization.
- Promote engineering excellence through code reviews, architecture discussions, and working with other developers from the cross-functional teams.
What We’re Looking For:
- 8+ years of experience as a full-stack software engineer with strong backend architecture skills.
- Deep experience with Java, Spring Boot, and microservices architecture.
- Experience working with real-time data ingestion into the risk engines in production.
- Proficiency in JavaScript/TypeScript and React for building full-stack applications.
- Familiarity with cloud-native infrastructure, especially AWS, and containerized services using Docker and Kubernetes.
- Strong understanding of CI/CD best practices and experience with GitHub Actions (or similar), deployment pipelines, and observability tools.
- Experience designing or integrating with third-party APIs, especially fraud vendors and data providers.
- Ability to work autonomously within a business unit and drive alignment across data science, product, and strategy teams.
- A collaborative and business-minded engineer who understands the “why” behind risk mitigation efforts and is motivated by impact.
Nice to Haves:
- Prior experience building case management systems or internal tools for manual operations.
- Exposure to fraud prevention, payments, trust & safety, or similar risk domains.
- Experience with building ML model feedback loops or event-driven architectures.
- Familiarity with Infrastructure as Code (e.g., Terraform).
- Experience working on small, high-impact teams embedded in cross-functional environments.
The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity.
For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.
Tags: APIs Architecture AWS CI/CD Docker Engineering Fraud risk GitHub Java JavaScript Kubernetes Machine Learning Microservices ML models Model training Pipelines React Terraform TypeScript
Perks/benefits: Team events
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