Cyber Manager
2 days ago
Houston, TX, United States
Deloitte
Full-time
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Position Summary
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 doAs 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 engagementA successful candidate would possess these
skills:
• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines
• Ability to mentor and provide clear guidance to othersThe teamDeloitte's Cyber Resilience practice helps organizations anticipate, withstand, and recover from disruption — spanning disaster recovery orchestration, business continuity and recovery planning, and third-party resilience, as well as the underlying architecture, inventory, monitoring, and control and evidence collection programs that demonstrate cybersecurity and continuity posture to regulators and stakeholders. The team is building AI-driven capabilities — including automated controls, continuous monitoring, response workflows, and audit-ready evidence generation — designed to help clients strengthen resilience posture, simplify complexity, and respond with greater speed and confidence when disruption occurs.
The FDE is embedded directly in a client's environment to build and ship AI capabilities using the client's own data, systems, and workflows, with resilience and recovery use cases (e.g., disaster recovery orchestration, control and evidence collection, response workflows, third-party resilience monitoring) as the applied domain for that AI engineering work. QualificationsRequired:
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; alternatively, equivalent demonstrated experience
• 8-10+ years of hands-on software engineering experience building and deploying production-grade systems using one or more of the following — Python, Java, or Node.js
• 5+ years of experience translating client or busine
Work you'll doAs 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 engagementA successful candidate would possess these
skills:
• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines
• Ability to mentor and provide clear guidance to othersThe teamDeloitte's Cyber Resilience practice helps organizations anticipate, withstand, and recover from disruption — spanning disaster recovery orchestration, business continuity and recovery planning, and third-party resilience, as well as the underlying architecture, inventory, monitoring, and control and evidence collection programs that demonstrate cybersecurity and continuity posture to regulators and stakeholders. The team is building AI-driven capabilities — including automated controls, continuous monitoring, response workflows, and audit-ready evidence generation — designed to help clients strengthen resilience posture, simplify complexity, and respond with greater speed and confidence when disruption occurs.
The FDE is embedded directly in a client's environment to build and ship AI capabilities using the client's own data, systems, and workflows, with resilience and recovery use cases (e.g., disaster recovery orchestration, control and evidence collection, response workflows, third-party resilience monitoring) as the applied domain for that AI engineering work. QualificationsRequired:
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; alternatively, equivalent demonstrated experience
• 8-10+ years of hands-on software engineering experience building and deploying production-grade systems using one or more of the following — Python, Java, or Node.js
• 5+ years of experience translating client or busine