Cyber - AI Cloud Security Engineer - Senior Consultant

Deloitte • Jersey City, NJ

1d • $105,400 - $207,800 • Onsite

About The Position

Deloitte is seeking an AI Cloud Security Engineer, Senior Consultant to design, build, and secure next-generation AI-enabled products, platforms, and cloud environments. This engineering-focused Senior Consultant role combines artificial intelligence (AI) security architecture, AI Zero Trust, secure AI software development, cloud security engineering, and AI-enabled vulnerability discovery and remediation. You will apply hands-on software engineering, cybersecurity, and cloud architecture experience to lead delivery of production-quality solutions that help clients build resilient AI platforms and embed security 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
• 3+ years of professional experience in software engineering, AI engineering, cybersecurity, cloud security, application security, or technology consulting, including hands-on experience designing and implementing software, AI, cloud security, or cybersecurity solutions
• Hands-on experience using 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

• Production experience securing Anthropic Claude, Claude Code, OpenAI, Google Gemini, Amazon Bedrock, or Vertex AI
• 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

Responsibilities

• Designing secure architectures for generative AI, agentic AI, retrieval-augmented generation (RAG), model-serving, and AI-enabled enterprise applications; defining security boundaries and applying AI Zero Trust controls across models, agents, tools, application programming interfaces (APIs), data, cloud workloads, development pipelines, and runtime environments
• Embedding security across the AI software development lifecycle through 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
• Designing and implementing secure AI workloads across Amazon Web Services, 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
• Building AI-assisted capabilities to identify, analyze, prioritize, test, and remediate vulnerabilities across code, applications, APIs, cloud configurations, infrastructure, dependencies, containers, and AI workloads; implementing human approval and validation before high-impact remediation is deployed
• Developing production AI security applications and platforms using user experiences, APIs, backend services, microservices, event-driven workflows, RAG, model integrations, observability, and unit, integration, end-to-end, performance, security, and AI evaluation testing
• Leading client discovery, architecture sessions, technical workshops, design reviews, deployment, and operational handoff; creating reusable reference architectures, technical standards, playbooks, and accelerators; mentoring engineers and contributing to practice development

Benefits

• Discretionary annual incentive program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior