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Develop and scale backend infrastructure for an AI-native cybersecurity platform. Responsibilities include designing software applications, writing clean and documented code, delivering and testing features, troubleshooting and debugging issues, reviewing peer code, and maintaining technical documentation. The role supports systems that monitor large volumes of digital entities and detect social engineering threats such as phishing, impersonation, and fraud.

Leads the Forward Deployed Engineering team, setting technical direction while remaining hands-on with strategic enterprise deployments. Owns customer onboarding from discovery through production, builds integrations across APIs, identity systems, email infrastructure, and security platforms, and converts deployment learnings into reusable product capabilities, automation, and tooling. Partners with customers, GTM, Product, and Engineering to resolve ambiguity, improve scalability, and shape the product roadmap.

The Software Engineer, Infrastructure will develop backend infrastructure for scalable monitoring of digital threats using AI, enhancing systems for faster deployment and reliability.

Develop and operate scalable backend systems for an AI-driven defense platform against digital threats, ensuring production reliability and collaborating across teams.

As a Machine Learning Engineer at Doppel, you will design, train, and deploy models for detecting malicious content, working with large datasets and collaborating with teams to ensure scalability and production readiness.

Build the Simulation product as a full‑stack engineer: design and ship AI-powered phishing simulations using LLMs and voice synthesis, create user flows for natural-language simulation creation, scale systems monitoring massive data, and iterate quickly with customers and product teams.