Company Overview:

Cellebrite’s (Nasdaq: CLBT) mission is to enable its global customers to protect and save lives by enhancing digital investigations and intelligence gathering to accelerate justice in communities around the world. Cellebrite’s AI-powered Digital Investigation Platform enables customers to lawfully access, collect, analyze and share digital evidence in legally sanctioned investigations while preserving data privacy. Thousands of public safety organizations, intelligence agencies and businesses rely on Cellebrite’s digital forensic and investigative solutions-available via cloud, on-premises and hybrid deployments-to close faster and safeguard communities.

To learn more, visit us at www.cellebrite.com, https://investors.cellebrite.com/investors and find us on social media @Cellebrite.

Position Overview

We are assembling a highly skilled, small-scale engineering team focused on transforming generative AI innovation into real, production-grade platforms. As a Platform Engineer with a strong backend orientation, you will architect and implement the core infrastructure that enables rapid deployment, experimentation, and scaling of advanced AI capabilities. Your work will bridge cutting-edge research with reliable, secure, high-performance systems powering the next generation of digital intelligence products.

Responsibilities

• Design and implement backend systems powering GenAI-driven applications

• Build cloud-native, scalable platforms for rapid AI prototyping and production deployment

• Develop high-performance microservices and APIs supporting real-time AI workloads

• Create adaptive architectures capable of integrating evolving AI models and technologies

• Collaborate with AI research teams to operationalize concepts into production-ready services

• Ensure system reliability, security, observability, and high availability

• Optimize performance, latency, and scalability of distributed services

• Drive experimentation with new technologies to push platform capabilities forward

• Build flexible infrastructures that evolve in parallel with emerging AI capabilities

Requirements:

• 5–7 years of backend or platform engineering experience
• B.Sc. or M.Sc. in Computer Science, Software Engineering, or related field
• Proven expertise in: Backend development (Node.js / Python preferred), Microservices and distributed architectures, Cloud platforms (AWS / GCP / Azure), API design and integration, Performance optimization and system scalability
• Experience designing robust, production-grade systems
• Deep understanding of event-driven or data-intensive architectures
• Ability to translate research-level concepts into practical, deployable technology
• Strong problem-solving mindset, with a passion for innovation and rapid iteration