Principle Software Engineer

Position Summary

This position is an exciting opportunity to join the Application Security division of Digital.ai, an industry leader specializing in client-side application protection. Our products embed security directly into applications, enabling them to defend themselves in untrusted environments. We are seeking a highly experienced Principal Software Engineer with expertise in modern web portal development, distributed event-processing systems, real-time analytics platforms, and AI/ML-driven data engineering workflows. The ideal candidate will help architect and optimize intelligent, data-intensive systems that support large-scale telemetry and security analytics. Experience with React, Node.js, Kafka, AWS Lambda, cloud-native engineering, and the use of AI/ML techniques to enhance data processing and insight generation is required.

What You Will Be Doing

You will join a team of cloud-native engineers building scalable, secure, and reliable cloud services powering our in-app protection products. Our services process billions of security events daily from more than 10 million devices worldwide.

As a full-stack Principal Engineer, you will:

• Drive architecture and implementation across the web stack, distributed systems, and AI-assisted analytics workflows.
• Leverage AI/ML techniques to strengthen event processing, anomaly detection, and data enrichment.
• Influence technical strategy across multiple teams, particularly around intelligent pipelines and analytics.
• Work in a fast-paced Agile/Scrum environment with frequent releases and high impact.

Primary Responsibilities

Web Application & Portal Engineering

• Lead the architectural design and development of scalable, secure web applications using React, Node.js, and TypeScript.
• Develop modular, maintainable UI components and back-end services aligned withengineering standards.
• Ensure adherence to performance, accessibility, and security best practices.Event Processing & Streaming Systems
• Architect and maintain distributed, event-driven systems using Apache Kafka, AWS Lambda, and related AWS services.
• Implement high-throughput pipelines for event ingestion, transformation, and enrichment.
• Apply AI-assisted techniques (e.g., automated anomaly scoring, content classification, behavioural clustering) to enhance streaming workflows.
• Ensure reliability, observability, and resilience across all streaming components.

Real-Time Analytics & Intelligent Data Engineering

• Design and support systems that deliver real-time analytics based on streaming and operational data.
• Collaborate with data engineering, analytics, and product teams to define schemas, telemetry models, KPIs, and AI-enriched data signals.
• Integrate lightweight ML models, heuristics, or AI-based scoring mechanisms intodashboards, alerts, and internal tools.
• Build data pipelines that support ML-assisted insights, including featurecomputation, data quality validation, and intelligent filtering.
• Work with ML frameworks or cloud AI services to ope