Forward Deployed AI Engineer for Cyber Security

As a Forward Deployed AI Engineer for Cyber Security, you will sit at the intersection of applied AI/LLM engineering and enterprise cybersecurity. You will be embedded directly with cybersecurity operational and engineering teams (Application Security, SecOps/SOC, Threat Intelligence, and Vulnerability Management) to build, deploy, and scale production-grade AI systems, LLM-powered pipelines, and autonomous agentic workflows that solve high-impact security challenges.

You are not just integrating APIs or using chat assistants—you are designing and shipping resilient, evaluated, tool-using LLM architectures and automated security capabilities directly into production environments within a global financial institution.

Key Responsibilities

• Build and Deploy LLM-Powered Security Systems: Architect, develop, and operationalize end-to-end AI applications, tool-augmented agents, and Retrieval-Augmented Generation (RAG) pipelines tailored to cybersecurity workflows (e.g., automated vulnerability remediation, intelligent SOC triage, SAST/DAST triage automation, and detection engineering).

• Embedded Problem Solving (Forward Deployed): Work directly with security practitioners (AppSec engineers, SOC analysts, incident responders, penetration testers) to deeply understand operational bottlenecks and translate complex security requirements into working AI software solutions.

• Agentic Workflows & Tool Integration: Design autonomous, evaluated, tool-using agent frameworks that interact securely with enterprise APIs, security scanners, SIEM/SOAR platforms, code repositories, and containerized infrastructure.

• Implement Robust AI Evaluation & Guardrails: Establish rigorous evaluation frameworks (benchmarking latency, accuracy, faithfulness, hallucination, tool-call precision) and implement input/output guardrails to ensure robust, deterministic behavior.

• Production Engineering & CI/CD: Write clean, modular, production-ready Python code. Package applications into containerized microservices and deploy via automated CI/CD pipelines following enterprise security and architecture standards.

• Secure the AI & Ensure AI Safety: Apply secure coding practices and implement defenses against AI-specific attack vectors, including prompt injection, model abuse, data leakage, and insecure tool execution. Keep safety and compliance non-negotiable from day one.

• Cross-Team Knowledge Sharing & Scaling: Standardize reusable AI components, evaluation patterns, and integration libraries across the broader CISO engineering organization to accelerate enterprise-wide adoption.

Levels We're Hiring For