Cyber Senior Manager - Technology Resilience FDE

Experteer Overview As a Senior Manager in Deloitte Cyber, you embed with a client to design and deliver production-grade AI capabilities using their data and systems, while leading engineering teams and the technical roadmap. You will shape AI solutions across multiple workstreams to enhance disaster recovery, control and evidence collection, and resilience monitoring. Your role combines deep engineering with people leadership to scale reusable accelerators and drive client outcomes. This position offers influence across engagements and the broader practice, with a clear focus on impact and audit-ready outcomes. Compensation / Benefits * Design and build AI-enabled solutions inside a client’s environment using live data and systems * Define and enforce production AI practices including evaluation, guardrails, observability, reliability, security, and cost/performance * Mentor and manage Engineering Managers and their teams across client engagements * Architect the AI capability roadmap across multiple workstreams for a client or portfolio * Engage client stakeholders (e.g., CISO, resilience and GRC leadership) to prioritize automation of controls and evidence workflows * Translate client needs into production-grade AI solutions, focusing on resilience use cases * Lead hands-on design, integration, deployment, and operation of production-grade solutions * Own technical solutioning during pursuits, including POCs, demonstrations, and pricing inputs * Own client enablement at scale through workshops, adoption planning, and training curricula * Manage client delivery across scope, timelines, quality, and customer satisfaction * Create reusable accelerators and scale adoption across teams with proper documentation * Own the technical roadmap across engagements and contribute to practice capability development Tasks * 12-15+ years of hands-on software engineering experience * Proficiency in Python, Java, or Node.js * 7+ years translating business requirements into target-state architectures (REST APIs, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, and version control * 3+ years designing and deploying generative AI/LLM solutions (agents, RAG, tool-calling) in production * Experience owning AI production practices across multiple engagements * 3+ years leading and developing engineering teams, including Engineering Managers * Experience architecting AI-enabled solutions across multiple workstreams * Contributing to practice capability beyond individual engagements (mentoring, hiring, training, reusable IP) * Ability to work independently inside a client environment and codebase * Ability to integrate automation with monitoring, ITSM, or GRC platforms * 25-50% travel availability Key requirements * discretionary annual incentive program * opportunities for professional development * accommodations for people with disabilities

and across multiple workstreams for a client or portfolio * Engage client stakeholders (e.g., CISO, resilience and GRC leadership) to prioritize automation of controls and evidence workflows * Translate client needs into production-grade AI solutions, focusing on resilience use cases * Lead hands-on design, integration, deployment, and operation of production-grade solutions * Own technical solutioning during pursuits, including POCs, demonstrations, and pricing inputs * Own client enablement at scale through workshops, adoption planning, and training curricula * Manage client delivery across scope, timelines, quality, and customer satisfaction * Create reusable accelerators and scale adoption across teams with proper documentation * Own the technical roadmap across engagements and contribute to practice capability development Tasks * 12-15+ years of hands-on software engineering experience * Proficiency in Python, Java, or Node.js * 7+ years translating business requirements into aaaaaa people architectures (REST APIs, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, and version control * 3+ years designing and deploying generative AI/LLM solutions (agents, RAG, tool-calling) in production * Experience owning AI production practices across multiple engagements * 3+ years leading and developing engineering teams, including Engineering Managers * Experience architecting AI-enabled solutions across multiple workstreams * Contributing to practice capability beyond individual engagements (mentoring, hiring, training, reusable IP) * Ability to work independently inside a client environment and codebase * Ability to integrate automation with monitoring, ITSM, or GRC platforms * 25-50% travel availability Key requirements * discretionary annual incentive program * opportunities for professional development * accommodations for people with disabilities