Cyber Senior Manager - Technology Resilience FDE

Deloitte France; Grand Rapids (MI); On-site; USD 189,000 - 373,000; Full time

Job summary

Deloitte is seeking a Technical Resilience FDE Senior Manager to lead embedded AI engineering efforts within client environments. You will design, build, and deploy production-grade AI capabilities, mentor engineers and engineering managers, and own the technical roadmap across multiple workstreams, including disaster recovery and resilience monitoring.

You will engage with CISOs and GRC leaders to prioritize automation of controls and evidence workflows, delivering scalable accelerators and

Qualifications

• Bachelor's degree in Computer Science, Engineering, IT, or related field.
• 12-15+ years hands-on software engineering building production-grade systems using Python, Java, or Node.js.
• 7+ years translating client requirements into target-state architectures using REST APIs, microservices, event-driven, or serverless patterns.
• 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, and version control.
• 3+ years designing and deploying generative AI or LLM solutions in client/production environments.
• Experience owning and setting standards for production AI engineering practices across engagements.
• 3+ years leading and developing engineering teams, including direct management of Engineering Managers.
• Experience architecting AI-enabled solutions across multiple workstreams.
• Contributing to practice capability, mentoring managers, and helping hiring/training.
• Owning client enablement at scale across engagements.

Responsibilities

• Designing and hands-on building AI-enabled solutions inside a client's environment.
• Setting and owning standards for AI production practices across multiple solutions.
• Leading and mentoring Engineering Managers and their teams.
• Architecting AI capability roadmaps across workstreams and domains.
• Engaging client stakeholders to prioritize automation of controls and evidence workflows.
• Translating client needs into production-grade AI solutions.
• Leading design, integration, deployment, and operation of production-grade solutions.
• Owning technical solutioning during pursuits including demonstrations and proofs of concept.
• Owning client enablement across engagements with workshops and training curricula.
• Managing client delivery including scope, timelines, and quality.
• Creating reusable accelerators and scaling adoption with documentation.
• Owning the technical roadmap across engagements and contributing to practice development.

Skills

AI Engineering

Leadership

Mentoring

Client engagement

Python

Java

Node.js

REST APIs

Microservices

Event-driven

Serverless

CI/CD

AWS

Azure

GCP

Observability

Security

Cost optimization

Education

Bachelor's degree

Relevant experience

Tools

AWS

Azure

GCP

Job description

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

• 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
• Setting and owning standards for AI production practices - evaluation, guardrails, observability, reliability, security, and cost/performance management - across 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 needs - including resilience use cases such 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 delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements
• Creating new reusable accelerators and scaling their adoption across teams and engagements, backed by documentation and knowledge transfer
• Owning the technical roadmap across engagements and contributing to broader practice capability development, including hiring, training curricula, and reusable IP

A 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
• Proven ability to mentor, develop, and manage the performance of other engineers and engineering managers

The team

Deloitte'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.

Qualifications

Required:

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; alternatively, equivalent demonstrated experience
• 12-15+ 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
• 7+ years of experience translating client or business requirements into target-state solution architectures using REST APIs, microservices, event-driven architectures, or serverless components
• 3+ years of experience delivering solutions on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including containers, continuous integration and continuous delivery pipelines, and version control tools
• 3+ years of hands-on experience designing, building, and deploying generative AI or large language model solutions (e.g., agents, RAG, tool-calling) in a client or production environment - beyond proof-of-concept
• Experience owning and setting standards for production AI engineering practices - evaluation, guardrails, observability, reliability, security, and cost/performance management - across multiple solutions or engagements
• 3+ years of experience leading and developing engineering teams, including direct management of Engineering Managers or equivalent technical leads, with accountability for performance management and career development
• Experience architecting AI-enabled solutions across multiple workstreams or operational domains, translating varied client requirements into a coherent technical roadmap
• Experience contributing to practice or team capability beyond individual engagements - for example, mentoring engineering managers, shaping hiring or training practices, or developing reusable accelerators and IP
• Experience owning client enablement at scale - workshops, demonstrations, adoption planning, and operational handoff - across multiple engagements or a portfolio of clients
• Experience creating new reusable AI accelerators, tools, or frameworks and driving their adoption and scaling across teams and engagements
• Ability to work directly and independently within a client's environment and codebase, including navigating unfamiliar systems and undocumented workflows
• Ability to build and oversee automation that integrates with monitoring, ITSM, or GRC platforms to support control monitoring, evidence collection, and response workflows across multiple engagements
• Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve
• Limited immigration sponsorship may be available

Preferred:

• Front-end / full-stack breadth - JavaScript/TypeScript and a modern UI framework (React / Next.js) for building demo apps and lightweight delivery tooling leveraging agentic coding tools (e.g., Claude Code, Codex, Cursor, etc.)
• Experience with agent orchestration or LLM application frameworks (e.g., LangChain, LlamaIndex, Model Context Protocol, Bedrock Agents, Azure AI Foundry, Vertex AI)
• Experience with GRC, ITSM, or monitoring/observability platforms (e.g., ServiceNow, Archer, Splunk, Datadog) at an architecture or platform-ownership level
• Familiarity with resilience-related frameworks or standards (e.g., NIST CSF, ISO 22301, SOC 2) useful for translating client requirements into engineering priorities - not an audit or compliance credential
• Experience designing AI-enabled use cases within resilience or continuity workflows (e.g., disaster recovery orchestration, control and evidence automation, third-party resilience monitoring) across multiple clients or engagements is a plus, though not a prerequisite
• Track record presenting technical roadmaps or audit-readiness outcomes to CISO, GRC, or other executive stakeholders
• Prior experience in a forward-deployed, embedded, or client-site engineering model (vs. offshore/remote delivery only)
• Industry depth in a regulated vertical (financial services, healthcare, public sector) and exposure to associated compliance regimes (SOX, PCI DSS, FFIEC, HIPAA, GDPR)
• Kubernetes, GitOps, and advanced cloud-native delivery patterns
• Familiarity with ML frameworks (PyTorch, TensorFlow) and model evaluation
• Relevant certifications - cloud (AWS/Azure/GCP) or AI/ML-specific certifications

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $189,200 - $372,900 .

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberCDR27

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.