Cyber Senior Manager - Technology Resilience FDE

Experteer Overview As a Senior Manager in Deloitte Cyber, you embed with clients to design, build, and deploy production-grade AI capabilities using their data and systems, while leading the engineering team and technical roadmap. You will shape AI solutions across resilience use cases like disaster recovery orchestration and evidence automation, aligning with client governance needs. This role combines deep hands-on engineering with leadership to drive scalable accelerators and impact across engagements. You will work closely with client stakeholders to deliver auditable, resilient AI capabilities that improve disruption response and recovery. Compensation / Benefits * Design and build AI-enabled solutions inside a client’s environment using live data and systems * Set and own standards for production AI practices including observability, security, and cost/performance * Mentor and manage the performance of Engineering Managers and their teams * Architect AI capability roadmaps across multiple workstreams and domains * Engage client stakeholders to prioritize automation of controls, monitoring, and evidence workflows * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and operation of solutions * Own technical solutioning during pursuits, including POCs and effort estimation * Enable clients at scale through workshops, adoption planning, and training curricula * Oversee client delivery quality, timelines, and satisfaction * Create reusable accelerators and scale adoption across engagements * Own the technical roadmap across engagements and contribute to capability development Tasks * Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field * 12-15+ years of hands-on software engineering experience * 7+ years translating requirements into target-state architectures (REST, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers and CI/CD * 3+ years building and deploying generative AI or LLM solutions in client/production environments * Experience owning AI engineering standards for evaluation, guardrails, observability, reliability, security, and cost/performance * 3+ years leading and developing engineering teams including managers * Experience architecting AI-enabled solutions across workstreams and roadmaps * Experience contributing to practice capability development, training, or reusable IP * Experience enabling client workshops, demonstrations, and handoffs across multiple engagements * Experience creating reusable AI accelerators and driving adoption * Ability to work independently within a client environment and navigate unfamiliar systems * Ability to travel ~25-50% Key requirements * discretionary annual incentive program

_ multiple workstreams and domains * Engage client stakeholders to prioritize automation of controls, monitoring, and evidence workflows * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and operation of solutions * Own technical solutioning during pursuits, including POCs and effort estimation * Enable clients at scale through workshops, adoption planning, and training curricula * Oversee client delivery quality, timelines, and satisfaction * Create reusable accelerators and scale adoption across engagements * Own the technical roadmap across engagements and contribute to capability development Tasks * Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field * 12-15+ years of hands-on software engineering experience * 7+ years translating requirements into target-state architectures (REST, microservices, event-driven, or serverless) * 3+ years delivering solutions on a and Azure, or GCP including containers and CI/CD * 3+ years building and deploying generative AI or LLM solutions in client/production environments * Experience owning AI engineering standards for evaluation, guardrails, observability, reliability, security, and cost/performance * 3+ years leading and developing engineering teams including managers * Experience architecting AI-enabled solutions across workstreams and roadmaps * Experience contributing to practice capability development, training, or reusable IP * Experience enabling client workshops, demonstrations, and handoffs across multiple engagements * Experience creating reusable AI accelerators and driving adoption * Ability to work independently within a client environment and navigate unfamiliar systems * Ability to travel ~25-50% Key requirements * discretionary annual incentive program