Cyber Manager - Technology Resilience

Technical Resilience FDE Manager

As a 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.

This role is administratively aligned to the Cyber Resilience practice, and the applied use cases you 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 AI engineering work supports, not prerequisites requiring deep resilience or audit domain credentials.

You will combine strong engineering depth with the judgment to translate ambiguous client problems into working AI systems, 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 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 and systems

• Ensuring deployed AI systems meet production bars for evaluation, guardrails, observability, reliability, security, and cost/performance management

• Building automated controls and response workflows that support disaster recovery orchestration and continuity and recovery operations

• Building AI-enabled control and evidence collection capabilities - automating inventory, monitoring, and evidence gathering to produce audit-ready evidence across cybersecurity, continuity, and third-party resilience programs

• Translating client business needs - including resilience use cases such as continuity planning and recovery orchestration - into working, production-grade AI technical solutions aligned to target architecture

• Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope

• Shaping technical solutions during pursuits by leading demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs

• Leading client-facing workshops, demonstrations, and training sessions to drive adoption of new AI capabilities, and supporting operational handoff so client teams can run and maintain what you build

• Managing client delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements

• Contributing to and extending existing reusable accelerators, documentation, and engineering best practices to build team and client capability

• Mentoring engineers and leading individual workstreams within the engagement

A successful candidate would possess these skills:

• Ability to work independently and collaborate as part of...