Cyber - AI Cloud Security Engineer - Manager

Deloitte•Jersey City, NJ

1d•$134,500 - $265,100•Onsite

About The Position

Deloitte is seeking an AI Cloud Security Engineer, Manager to lead the design, implementation, and security of artificial intelligence (AI)-enabled products, platforms, and cloud environments. This engineering-focused Manager role combines AI security architecture, AI Zero Trust, secure AI software development, cloud security engineering, and AI-enabled vulnerability discovery and remediation. You will lead technical delivery for complex client programs, apply hands-on software engineering, cybersecurity, and cloud architecture expertise, and guide teams in building resilient AI platforms with security embedded throughout the technology lifecycle.

Requirements

Bachelor’s degree in Information Technology, Computer Science, Artificial Intelligence, Cybersecurity, Computer Engineering, or Software Engineering; equivalent professional work experience in software engineering, AI engineering, cybersecurity, cloud security, application security, or technology consulting may be considered in lieu of a degree
6+ years of professional experience in software engineering, AI engineering, cybersecurity, cloud security, application security, or technology consulting, including leadership of AI, software engineering, cloud security, cybersecurity, or technology transformation programs
Hands-on experience with at least one of the following AI platforms: Anthropic Claude, Claude Code, OpenAI, Google Gemini, Amazon Bedrock, or Vertex AI
Experience designing or implementing cloud security architecture, secure application development, development, security, and operations (DevSecOps), infrastructure security, or AI security controls
Experience developing and deploying APIs, database-backed services, distributed systems, or cloud applications using Python, TypeScript, JavaScript, Go, or Java, including automated testing, deployment, and observability
Ability to travel up to 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Nice To Haves

Experience securing Anthropic Claude, Claude Code, OpenAI, Google Gemini, Amazon Bedrock, or Vertex AI in production environments
Experience designing AI Zero Trust architectures or implementing security controls for models, agents, tools, data, and AI runtime environments
Experience conducting AI red teaming, adversarial testing, model evaluation, prompt security testing, RAG security testing, or responsible AI control testing
Experience developing applications using React, Next.js, Node.js, FastAPI, GraphQL, Representational State Transfer (REST) APIs, microservices, or event-driven systems
Experience implementing policy-as-code, infrastructure-as-code security, or automated remediation using Terraform, Open Policy Agent, Checkov, tfsec, Kyverno, static application security testing (SAST), dynamic application security testing (DAST), software composition analysis, secrets scanning, or container security tools
Experience securing Kubernetes, containers, serverless platforms, cloud-native applications, or software supply chains; or delivering AI, cybersecurity, cloud, or application security solutions for financial services or healthcare organizations

Responsibilities

Leading the design of secure architectures for generative AI, agentic AI, retrieval-augmented generation (RAG), model serving, and AI-enabled enterprise applications; defining security boundaries and AI Zero Trust controls across models, agents, tools, application programming interfaces (APIs), data, cloud workloads, development pipelines, and runtime environments
Establishing and implementing security practices across the AI software development lifecycle, including threat modeling, security gates, model and prompt versioning, evaluation datasets, approval workflows, release criteria, and testing for prompt injection, data leakage, unsafe tool use, model abuse, and policy violations
Leading the design and implementation of secure AI workloads across Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and hybrid environments, including cloud landing zones, network isolation, private connectivity, logging, encryption, key management, data protection, containers, serverless workloads, Kubernetes, and infrastructure-as-code controls
Directing AI-assisted vulnerability and threat management capabilities that identify, analyze, prioritize, test, and remediate issues across code, applications, APIs, cloud configurations, infrastructure, dependencies, containers, and AI workloads; establishing human approval and validation before high-impact remediation is deployed
Designing and building production AI security applications and platforms using full-stack engineering, including user experiences, APIs, backend services, microservices, event-driven workflows, RAG, model integrations, observability, and automated testing
Leading client discovery, architecture sessions, technical workshops, design reviews, program delivery, production deployment, and operational handoff; managing technical workstreams, mentoring engineers, and creating reusable reference architectures, standards, playbooks, and accelerators