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Salary: USD 100,000 - 250,000 / annual
Cogent Security is an Applied AI Lab building next-generation AI agents for cybersecurity. The company partners with Fortune 500 organizations to secure complex production environments, combining frontier research with real-world execution. The team includes talent from top universities (Stanford, Berkeley, Penn, Duke, Carnegie Mellon, Waterloo), high-growth companies (Scale AI, Databricks, Stripe, Tesla, Coinbase), cybersecurity leaders (Wiz, Abnormal AI, Zscaler), and research labs (DeepMind, SAIL). The company is backed by Greylock.
As a Forward Deployed Agent Engineer, you will design, build, and deploy mission-critical AI agents that operate in complex customer environments and drive measurable security outcomes. This is a highly cross-functional, forward-deployed role working directly with customers to understand their needs, adapt the platform to their environment, and continuously iterate on solutions that scale to millions of real-world events.
Key responsibilities include:
- Design and deploy security-focused AI agents that reason over large datasets, interact with security systems, and handle complex real-world workflows
- Own technical delivery end-to-end for new and existing customers, from data ingestion and transformation pipelines to configuration, workflow design, and feature extension
- Experiment with, evaluate, and integrate the latest text, voice, and multi-modal models into production environments
- Work directly with customer security teams to integrate agents with their tools, processes, and data sources
- Identify cross-customer trends and translate field insights into platform improvements and new capabilities
- Debug deep in the stack, investigate edge cases, and ensure agents meet enterprise-grade reliability and performance standards
Requirements:
- 2+ years of professional software engineering experience, ideally in high-velocity or customer-facing environments
- Proficiency in Python and TypeScript, with strong skills in asynchronous programming and building robust data integrations
- Strong debugging and systems thinking abilities; comfortable tracing issues across multiple layers of a stack
- Clear communication skills, with the ability to translate between technical and non-technical contexts
- Ability to thrive in ambiguity, take ownership end-to-end, and prioritize customer outcomes
Nice to have:
- Experience with multi-modal AI models, enterprise SaaS, security operations, or behavioral analytics
- Familiarity with large-scale data ingestion, transformation pipelines, and real-time processing
