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Fisher & Phillips LLP

AI Security Engineer

Atlanta, GA, United States

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Job details

Experience: 5+ years of security engineering, application/product security, cloud security, software security, or related cybersecurity experience.
Posting language: English
Posted: Oct 30, 2026

Original job description

(Atlanta, Full-time, Hybrid) - Must reside in the Atlanta area

Fisher Phillips, a premier international labor and employment law firm is seeking an experienced AI Security Engineer to design, implement, and continuously improve security controls for enterprise artificial intelligence, machine learning, and generative AI systems. This role is responsible for securing AI platforms, models, data pipelines, integrations, agents, and supporting cloud and SaaS environments throughout the AI lifecycle.

Position Summary

The AI Security Engineer will serve as a hands-on security specialist and trusted technical partner to cybersecurity, IT, data, application, privacy, compliance, and business teams. The ideal candidate combines security engineering experience with practical knowledge of AI/ML technologies, cloud security, secure development, threat modeling, and risk-based decision-making.

Key Responsibilities

AI Security Architecture & Strategy

Design and maintain security architecture for generative AI, machine learning, AI-enabled SaaS applications, agents, APIs, and supporting cloud services.
Establish security standards, reference patterns, and guardrails for AI development, deployment, integration, and use.
Perform security reviews and threat modeling for AI solutions, including model access, data flows, retrieval-augmented generation, plugins, tools, agents, and third-party integrations.
Evaluate AI technologies, models, vendors, and services to ensure security and privacy requirements are incorporated into design and implementation.

AI/ML Platform & Application Security

Implement controls to protect AI platforms, model endpoints, APIs, orchestration layers, vector databases, development environments, and supporting cloud infrastructure.
Assess and reduce risks such as prompt injection, sensitive data exposure, insecure tool use, excessive agency, model supply-chain compromise, and unauthorized AI usage.
Partner with application and platform teams to embed secure development, testing, secrets management, logging, and vulnerability remediation into AI solutions.

Data, Model & Identity Protection

Apply least privilege, strong authentication, service identity, privileged access, and lifecycle controls to AI platforms, models, agents, and workloads.
Protect training, grounding, prompt, output, and telemetry data using data classification, encryption, DLP, access controls, and appropriate retention practices.
Review model and agent permissions, data access, connectors, and tool integrations to identify excessive privileges, unsafe trust relationships, and unintended data exposure.

AI Security Engineering & Monitoring

Implement and optimize security controls for AI systems, including model gateways, content filtering, runtime guardrails, API security, cloud security, SIEM, DLP, and monitoring.
Develop detections and response procedures for AI-related misuse, policy violations, data leakage, anomalous model activity, and compromised integrations.
Automate security validation, testing, monitoring, and enforcement using Python, PowerShell, APIs, CI/CD, infrastructure-as-code, or orchestration tools.

Governance, Risk & Collaboration

Partner with compliance, privacy, legal, data, and business stakeholders to align AI security controls with policies, client expectations, governance requirements, and organizational risk objectives.
Develop documentation for AI security standards, architecture decisions, threat models, control designs, risk exceptions, and remediation plans.
Support AI risk assessments, incident investigations, tabletop exercises, and reviews of emerging AI threats, vulnerabilities, and attack techniques.
Communicate AI security risks and recommendations clearly to technical and non-technical stakeholders.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).
5+ years of security engineering, application/product security, cloud security, software security, or related cybersecurity experience.
Hands-on experience securing generative AI and LLM systems, including RAG, agents, model/API integrations, and enterprise AI platforms.
Experience with threat modeling, secure design/SDLC, application/API security testing, IAM, secrets management, and security logging/monitoring.
Proficiency in Python or another programming/scripting language; experience with APIs, automation, CI/CD, or security tooling.
Knowledge of AI threats and mitigations, including prompt injection, data leakage/poisoning, model extraction, insecure tool use, excessive agency, and AI supply-chain risk; familiarity with cloud AI services.

Preferred Qualifications

Experience with AI red teaming, adversarial testing, abuse-case analysis, or security evaluations of LLM, RAG, and agentic systems.
Experience with vector databases, model gateways, LangChain/LlamaIndex, MCP, and major cloud AI services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Familiarity with the OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF; experience with IaC, policy-as-code, containers, or CI/CD security is a plus.
Relevant security, cloud, or AI certifications; experience in a law firm, professional services, regulated industry, or client-service environment is preferred.

Key Competences

Strong hands-on security engineering, coding, and analytical problem-solving skills
Strong threat-modeling and adversarial thinking for AI, LLM, RAG, and agentic systems
Ability to translate AI use cases and emerging risks into secure, practical technical controls
Strong automation skills using scripting, APIs, and modern engineering workflows
Clear communication with technical and non-technical stakeholders
Sound judgment, intellectual curiosity, and a continuous-learning mindset

Why Join Us

At Fisher Phillips, we recognize that exceptional talent is the foundation of our success, enabling us to deliver outstanding service to both our internal and external clients. Joining our team means collaborating in a professional yet dynamic environment that leverages cutting-edge technology. Our leadership is committed to fostering your professional growth and providing opportunities to challenge yourself in meaningful ways.

We believe in rewarding talent with more than just a competitive salary. Our comprehensive benefits package includes health, dental, and vision insurance, a 401(k) with profit sharing, generous paid time off, and holidays.

Your well-being is our priority. We offer 24/7 telehealth services, a variety of wellness programs, and additional optional benefits designed to support your unique lifestyle. At Fisher Phillips, you’ll find a workplace that values your health, happiness, and continued professional development. To learn more about our firm, visit us at www.fisherphillips.com.

Equal Opportunity Employer

Fisher Phillips is committed to providing equal employment opportunities to all employees and applicants, regardless of race, ethnicity, religion, sex (including related medical conditions), gender, sexual orientation, national origin, citizenship status, veteran status, marital status, pregnancy, age, disability, or any other protected status, in compliance with all applicable laws.

The statements in this position description are not necessarily all-inclusive. Additional duties and responsibilities may be assigned, and requirements may vary from time to time.

Relocation costs are not covered. We are only accepting direct applicants; third-party recruiters or agencies will not be considered. No phone inquiries, please.

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