Job description

About the position Are you passionate about technology and interested in joining a community of collaborative colleagues who respectfully and courageously seek to challenge the status quo? If so, read on to learn more about an exciting opportunity with Deloitte Technology US (DT - US). We are curious and life-long learners focused on technology and innovation. The AI Security Engineer for GPS Operations will partner with Government Public Sector (GPS) Cyber Teams to deliver AI enabled solutions and capabilities protecting our Firm and our clients. Our Security Architecture, Engineering, and Operations Teams are developing and deploying innovative and industry leading AI solutions in all facets of Cyber Security. The AI Cyber Security Engineer for GPS Operations lead the effort to model, configure, test, and integrate AI solutions to deliver world class cyber security services and capabilities. This role is pivotal in leveraging Data and AI technologies, requiring a deep understanding of Cyber Security, Governance, Data Science, Statistics, Machine Learning, Generative AI, Large Language Models (LLMs), and Multimodal models. The AI Security Engineer will provide subject matter expertise, technical insight, and develop cyber and AI solutions that will drive and sustain Cyber Security excellence. Responsibilities • Represent GPS Cyber Operations AI/ML/GenAI technical direction, service delivery, and support alignment to organizational goals and digital transformation efforts. , • Translate operational requirements into realistic technical implementations, while identifying misaligned initiatives and impractical use cases. , • Key contributor in creating a comprehensive AI Cyber Security framework for GPS supporting the deployment, evaluation, and management of ML models & GenAI solutions. , • Configure Cyber Security and AI technologies integrating with existing tools and capabilities. , • Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and security infrastructure that may leverage machine learning and large language models. , • Collaborate with Enterprise, Application, Data & DevOps Architects, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss Cyber Security Engineering. , • Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements. , • Be responsible for the successful execution of AI-powered applications using agile methodology. , • Audit AI tools and practices across data, models, and software engineering, focusing on continuous improvement and feedback mechanisms. , • Work closely with Cyber Security and Application Engineers to foresee and mitigate risks, ensure ethical AI implementation and compliance with established standards, norms, and regulations. , • Help Cyber Security and GPS Stakeholders understand the potential and limitations of AI when reviewing, testing, or integrating AI solutions. , • Create or review Cyber Security use-cases and broaden our collective understanding of leading AI technologies, analytics methods, tools, and operating models. Requirements • Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration. , • Minimum 5 years of experience with Cyber Security Architecture or Engineering. , • Minimum 2 years of experience building GenAI environments. , • Must be able to obtain US Government security clearance. , • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. , • Ability to travel up to 10%, on average, based on the work you do and the clients and industries/sectors you serve. Nice-to-haves • Advanced degrees preferred. , • Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect. , • Experience gathering non-functional requirements, performing designed and validated application architecture frameworks, and executing functional and testing assignments. , • Experience translating requirements into design documents. , • Experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft, and Azure. Benefits • Broad range of benefits including well-being programs. , • Opportunities for professional development and career growth. , • Flexible work environment.

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