Cyber Senior Manager - Technology Resilience FDE

Technical Resilience FDE Senior Manager As a Senior Manager, AI Engineering (Forward Deployed Engineer) in Deloitte Cyber, you will be embedded in a client's environment to design, build, and ship production-grade AI capabilities using the client's own data, systems, and workflows, while also leading the broader team and technical roadmap delivering that work. This role is administratively aligned to the Cyber Resilience practice, and the applied use cases you and your team build will typically span disaster recovery orchestration, control and evidence collection, continuity and recovery planning, and third-party resilience monitoring — but these are application areas your engineering and leadership work supports, not prerequisites requiring deep resilience or audit domain credentials. You will combine strong personal engineering depth with the ability to lead and develop other engineers, own the technical roadmap across multiple workstreams, shape technical solutions during pursuits, and build reusable accelerators that raise the bar across engagements. Recruiting for this role ends on 12/31/2026. Work you'll do As a Senior Manager on a client-embedded AI engineering team, you will be responsible for: • Designing and hands-on building AI-enabled solutions (agents, retrieval/RAG pipelines, automation workflows) directly inside a client's environment, using their live data a [... source excerpt omitted ...] multiple solutions or engagements • Leading, mentoring, and managing the performance and career development of one or more Engineering Managers and their teams across one or more client engagements • Architecting the AI capability roadmap across multiple workstreams or operational domains for a client or portfolio of clients — applied, for example, to disaster recovery orchestration, control and evidence automation, and third-party resilience monitoring • Engaging client stakeholders (e.g., CISO, resilience and GRC leadership) to prioritize automation of controls, monitoring, and evidence workflows that support their audit and compliance needs • Translating client business [... source excerpt omitted ...] as continuity planning and recovery orchestration — into working, production-grade AI technical solutions • Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope • Owning technical solutioning during pursuits, including demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs across multiple opportunities • Owning client enablement across engagements — workshops, demonstrations, adoption planning, operational handoff, and training curricula — so client teams can independently operate and extend delivered AI capabilities • Managing client