Senior Software Engineer – AI

About Cyble

Cyble is revolutionizing the landscape of cybersecurity intelligence. Founded in 2019, Cyble began as a visionary college project and has quickly transformed into a leading force in proactive cyber threat detection and mitigation, that is now globally significant, with people in 20 countries - Headquartered in Alpharetta, Georgia, and with offices in Australia, Malaysia, Singapore, Dubai, Saudi Arabia and India

Our mission is clear: to provide visibility, intelligence and cybersecurity protection using cutting-edge advanced technology, giving enterprises a powerful advantage. We democratize real-time intelligence about cyber threats and vulnerabilities, enabling organizations to take proactive measures and maintain robust cybersecurity. We strive to make the digital world a safer place for everyone.

At Cyble, artificial intelligence (AI) and innovation are central to all operations, with a commitment to continuous improvement and excellence in both products and business practices. Cyble values inclusivity, offering team members autonomy and flexibility to balance their professional and personal lives. Cyble fosters a culture where employees voices are heard, contributions are recognized, and everyone is encouraged to be part of something extraordinary.

About the Role

Cyble is building a cloud-native, AI-first cybersecurity intelligence platform that operates at global scale. We are looking for a Senior Software Engineer who is deeply hands-on and AI-native in how they think, design, and build systems.

This role is for engineers with 6–8 years of experience who can design and build scalable SaaS services with AI embedded as a core capability — not as an afterthought. You will work on distributed systems, real-time data pipelines, and LLM-powered, agentic workflows that automate analysis, triage, and decision-making across the platform.

What You’ll Do at Cyble:

AI-Native Engineering

Design and implement AI-driven backend services using LLMs for summarization, classification, enrichment, reasoning, and automated decision flows.

Build and operate RAG pipelines, embedding workflows, and vector search layers to power intelligent features.

Implement agentic AI patterns for autonomous workflows (triage, correlation, remediation), with strong guardrails and observability.

Partner with AI/ML engineers to productionize models and inference services in a secure, scalable manner.

Platform & Service Development

Design, build, and maintain microservices and APIs for a multi-tenant SaaS platform using Go, Node.js (TypeScript), or Python.

Contribute to system design, domain modeling, and service decomposition, aligning with platform-level architecture.

Build event-driven systems using Kafka, RabbitMQ, or cloud-native messaging services (SNS/SQS).

Implement ingestion and processing pipelines for external feeds, logs, and signals, including normalization and enrichment.

Cloud, Reliability & Security

Containerize and deploy services using Docker and Kubernetes; build and maintain CI/CD pipelines.

Ensure high availability, observability, and performance using modern monitoring and alerting stacks.

Apply secure-by-design principles, threat modeling, and compliance controls throughout development.

Collaboration & Technical Leadership

Collaborate closely with product, frontend, data, DevOps, and AI teams to deliver end-to-end capabilities.

Participate in architecture discussions, design reviews, and code reviews.

Mentor junior engineers and model a culture of ownership, innovation, and bias for action.

What You’ll Need:

6–8 years of professional backend or platform engineering experience.

Hands-on, recent experience building AI/LLM-powered features in production systems.

Strong understanding of LLM integration patterns: RAG, embeddings, prompt strategies, agents, and safety guardrails.

Proficiency in Go, Node.js (TypeScript), or Python (FastAPI/Flask/Django).

Solid grounding in distributed systems, microservices architecture, and