Senior Manager, Cybersecurity Engineer - AI & Application Protection

adpinternalcareers; Roseland (NJ); Hybrid; USD 170,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

ADP seeks a Senior Manager, Cybersecurity Engineer to lead an engineering team focused on protecting Generative AI, agentic apps, and modern environments. You will shape security strategy, mentor engineers, and drive scalable production capabilities in a fast-moving AI landscape.

Ideal candidates have strong leadership, hands-on AI security experience, and a track record of delivering secure, reliable software in cloud-native environments. Applies to hybrid work.

Qualifications

• Significant experience leading software/platform/DevSecOps/security engineering teams.
• Hands-on experience with Generative AI, LLMs, or agentic systems.
• Ability to mentor engineers and translate security risks into actionable plans.

Responsibilities

• Lead and develop engineers across AI and application protection engineering.
• Drive GenAI guardrails, LLM security controls, and agentic security initiatives.
• Translate ambiguous problems into clear priorities and engineering plans.

Skills

Leadership

AI & GenAI

Security engineering

Software development

Cloud platforms

Education

Bachelor's degree in CS/Engineering

Tools

Kubernetes

Docker

AWS

Azure

GCP

Job description

ADP is Hiring aSenior Manager, Cybersecurity Engineer - AI & Application Protection

In this role, you will lead a highly capable engineering team responsible for designing, building, and scaling protective security capabilities for **Generative AI, agentic applications, and modern application environments**. You will help turn ambiguous and rapidly evolving security problems into clear engineering priorities while developing engineers and creating opportunities for them to contribute in meaningful ways.

You will work closely with engineers on the development and maturity of ADP's GenAI Guardrails and application protection controls while helping drive emerging work in **agentic development security, LLM-driven security scanning, security evaluation, developer enablement, and other greenfield AI initiatives**. You will be expected to understand the technology deeply enough to challenge assumptions, guide technical decisions, and contribute directly when appropriate.

You will lead a team with responsibilities spanning software development, DevSecOps, security policy and scanner tuning, platform engineering, and application engagement. Our mission is simple - **build systems to automate repetition while keeping the human in the loop for novel decisions - so that we can continue to mature at the pace of AI.**

This role is ideal for an experienced engineering leader with significant AI and software development experience who enjoys growing people, solving ambiguous technical problems, and helping teams turn new ideas into scalable production capabilities.

Candidates coming from software or platform engineering leadership rather than a dedicated cybersecurity organization are encouraged to apply. Successful candidates will need to demonstrate a strong **security mindset**, significant practical understanding of AI technologies and risks, and the ability to rapidly develop deeper expertise as the threat and technology landscape evolves.

Like what you see?

Learn more about ADP at tech.adp.com/careers

RESPONSIBILITIES

• Lead, coach, and develop engineers working across AI and application protection engineering
• Drive execution across **GenAI guardrails, LLM security controls, agentic security, application protection, and emerging AI development workstreams**
• Translate ambiguous technical and security problems into clear priorities, ownership, and engineering plans
• Help evaluate emerging AI and agentic risks and guide practical engineering approaches to reduce those risks
• Partner closely with engineers on architecture, design, development, scanner and policy tuning, automation, and production maturity
• Manage engineering capacity, priorities, dependencies, delivery, performance, and career development
• Create scalable approaches for engaging application and development teams as adoption grows
• Balance greenfield engineering with reliability, technical debt, operational maturity, and existing production responsibilities
• Provide technical leadership through architecture and design reviews, technical problem solving, and hands‑on contribution when appropriate

To Succeed in This Role

You’ll have abachelor’s degree in a relevant field such as computer science, computer engineering, information technology, cybersecurityor equivalent experience.

EXPERIENCE:

• Significant experience leading software, platform, DevSecOps, or security engineering teams
• **Hands-on experience developing with or leading engineering for Generative AI**, including LLM APIs, agentic systems, RAG, tool use, or similar AI application patterns
• Demonstrated experience developing and growing technical engineers
• Strong understanding of AI risks including **prompt injection, unsafe model behavior, sensitive-data exposure, and tool/agent abuse**
• Experience with application security, AI security, or security engineering is preferred
• Experience leading multiple technical workstreams with changing priorities and ambiguous requirements

TECHNICAL SKILLS:

• Strong understanding of modern software engineering and the ability to read, review, and discuss production code in languages such as **Python, Java, Go, C#, or TypeScript/JavaScript**
• Practical understanding of **LLM architectures, agentic development patterns, APIs, security controls, and AI evaluation**

What are you waiting for?

Find out why people come to ADP and why they stay: https://youtu.be/ODb8lxBrxrY

(ADA version: https://youtu.be/IQjUCA8SOoA )

• Experience with modern DevSecOps practices including source control, automated testing, CI/CD, and production deployment
• Experience with public cloud technologies such as **AWS, Azure, or GCP**
• Experience with containerized services including **Kubernetes and Docker**
• Strong understanding of APIs, distributed systems, observability, telemetry, and production troubleshooting
• Ability to quickly learn emerging technologies and determine where experimentation should become scalable engineering

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