Full Stack Engineer - Internal Audit

About the Role

Reporting to the Senior Director of Cybersecurity and Technology Audit, you will join the growing Bengaluru Internal Audit Engineering team. You will build the applications, platforms, and user interfaces that power Cloudflare’s automated assurance strategy, partnering closely with AI/Data Science engineers and Internal Auditors to develop production-ready internal platforms.

Responsibilities

• Build the Future of Assurance: Develop end-to-end (full stack) applications that automate control testing and risk monitoring across global infrastructure.
• Data-driven Audit Execution: Leverage data science and advanced analytics to execute data-driven testing throughout the audit lifecycle.
• Customer Zero Engineering: Build and maintain internal tools and dashboards using Cloudflare’s stack (e.g., Workers, KV, D1, AI Gateway).
• AI-Driven Risk Detection: Integrate LLMs and machine learning pipelines to analyze vast datasets for anomalies, security misconfigurations, or compliance deviations.
• Engineer for Scale: Build high-availability microservices that pull data from APIs, databases, and production logs to deliver near real-time risk insights.
• Data Strategy: Partner with Data Engineers to ensure clean, actionable telemetry for continuous auditing.
• Own the Stack: Take full ownership of the lifecycle—from database schema design and API development to UI implementation and production deployment.

Desirable Skills, Knowledge, and Experience

• Bachelor’s or master’s degree in Computer Science, Software Engineering, or equivalent experience.
• 5+ years of full stack software engineering experience in a large-scale, high-throughput, distributed systems environment.
• Strong experience with backend languages (Python, Go, or Node.js) and modern frontend frameworks (React or TypeScript).
• Deep understanding of SQL/NoSQL databases, API design (REST/GraphQL), and distributed systems.
• Hands-on experience with cloud-native architectures (Cloudflare Workers, AWS, or GCP preferred).
• Familiarity with data engineering pipelines (ETL/ELT) and leveraging LLMs/ML for automated data analysis.
• Interest in technology risk management, internal audit methodologies, or engineering compliance frameworks.
• Ability to explain complex technical risks to non-technical stakeholders.