Senior Engineer – Generative AI & Security

Senior Engineer – Generative AI & Security

Location: Phoenix, AZ

Role Overview

We are seeking a Senior Engineer with deep expertise in Generative AI and cybersecurity to design, build, and secure enterprise-grade AI systems. The ideal candidate will have hands-on experience building AI agents, integrating LLM-driven systems into enterprise environments, and implementing robust security automation across the SDLC.

This role focuses on secure AI architecture, AI-driven security tooling, and automation of security governance within CI/CD pipelines.

Key Responsibilities

• Design and develop secure Generative AI and agentic AI solutions for enterprise use cases

• Build and deploy AI agents using frameworks such as LangGraph, AutoGen, or CrewAI

• Integrate AI systems with enterprise applications and security platforms

• Develop and maintain security automation tooling

• Implement GitHub workflow integrations and automate security checks within CI/CD pipelines

• Automate secure design reviews and enforce security guardrails in development workflows

• Identify and mitigate AI-specific security risks, including prompt injection, data leakage, and model misuse

• Apply OWASP Top 10 principles to both traditional and AI-driven systems

Required Qualifications

• 10+ years of software engineering experience

• 5+ years of hands-on cybersecurity experience

• 2+ years of experience working with Generative AI systems

• Strong proficiency in Python

• Working knowledge of JavaScript and Bash

• Experience with AI orchestration frameworks such as LangGraph, AutoGen, or CrewAI

• Deep understanding of OWASP Top 10 and AI security vulnerabilities

• Experience securing APIs, microservices, and cloud-native applications

• Strong experience with CI/CD pipelines and DevSecOps practices

Preferred Qualifications

• Experience with Go, Rust, or Java

• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform)

• Experience implementing enterprise-scale AI governance frameworks

• Knowledge of secure model deployment and AI risk assessment methodologies

Nice to Have

• Prior experience building internal AI platforms

• Experience integrating LLMs into enterprise security tools

• Background in secure SDLC automation