Cyber Senior Manager - Technology Resilience FDE

Experteer Overview As a Senior Manager in Deloitte Cyber, you embed in client environments to design, build, and deploy production-grade AI solutions using the client’s data and systems, while leading engineers and shaping the technical roadmap. You will work across resilience use cases such as disaster recovery orchestration, control and evidence automation, and third-party resilience monitoring. You combine deep engineering with people leadership to scale reusable accelerators across engagements. This role offers high-impact work at the intersection of AI and cyber resilience with direct client impact. Compensation / Benefits * Design and prototype AI-enabled solutions (agents, retrieval/RAG pipelines, automation workflows) inside client environments * Set and enforce AI production practices including evaluation, guardrails, observability, reliability, security, and cost/performance * Mentor and manage Engineering Managers and teams across client engagements * Architect AI capability roadmaps across multiple workstreams * Engage client stakeholders (CISO, resilience and GRC leadership) to automate controls, monitoring, and evidence workflows * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and troubleshooting of production-grade solutions * Own technical solutioning during pursuits: demos, PoCs, prototypes, effort estimation, pricing inputs * Oversee client enablement across engagements: workshops, adoption planning, handoff, and training curricula * Manage delivery across scope, timelines, quality, and customer satisfaction * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to broader capability development (hiring, training, IP) Tasks * 12-15+ years of hands-on software engineering experience * Proficiency in Python, Java, or Node.js * 7+ years translating requirements into target-state architectures (REST, microservices, event-driven, serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, version control * 3+ years designing/deploying generative AI or LLM solutions in production * Experience setting standards for production AI practices across multiple engagements * 3+ years leading and developing engineering teams including Engineering Managers * Experience architecting AI-enabled solutions across multiple workstreams * Experience contributing to practice capability, mentoring managers, shaping hiring/training, or developing reusable IP * Experience owning client enablement at scale across engagements * Experience creating reusable AI accelerators/tools/frameworks and scaling them Key requirements * discretionary annual incentive program * accommodations for disabilities during recruiting * opportunities for professional development * mentorship and training programs * collaborative, inclusive culture * career growth across engagements

roadmaps across multiple workstreams * Engage client stakeholders (CISO, resilience and GRC leadership) to automate controls, monitoring, and evidence workflows * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and troubleshooting of production-grade solutions * Own technical solutioning during pursuits: demos, PoCs, prototypes, effort estimation, pricing inputs * Oversee client enablement across engagements: workshops, adoption planning, handoff, and training curricula * Manage delivery across scope, timelines, quality, and customer satisfaction * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to broader capability development (hiring, training, IP) Tasks * 12-15+ years of hands-on software engineering experience * Proficiency in Python, Java, or Node.js * 7+ years translating requirements into aaaaaa direct architectures (REST, microservices, event-driven, serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, version control * 3+ years designing/deploying generative AI or LLM solutions in production * Experience setting standards for production AI practices across multiple engagements * 3+ years leading and developing engineering teams including Engineering Managers * Experience architecting AI-enabled solutions across multiple workstreams * Experience contributing to practice capability, mentoring managers, shaping hiring/training, or developing reusable IP * Experience owning client enablement at scale across engagements * Experience creating reusable AI accelerators/tools/frameworks and scaling them Key requirements * discretionary annual incentive program * accommodations for disabilities during recruiting * opportunities for professional development * mentorship and training programs * collaborative, inclusive culture * career aaa

• across engagements