Cyber Senior Manager - Technology Resilience FDE

Deloitte T.T.L.
Raleigh, NC, United States
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Continuous Integration Disaster Recovery Software Engineering Large Language Models Build Management Restful APIs Serverless Computing Microservices

Job description

Experteer Overview In this role you will embed within a client’s environment to design, build, and deploy production-grade AI capabilities using the client’s data and systems while leading the engineering team and technical roadmap. You’ll work across resilience-related domains such as disaster recovery, control and evidence automation, and third-party monitoring to drive secure, auditable AI solutions. You will shape solutions, mentor engineers, and deliver scalable accelerators that lift engagement impact. This position offers hands-on delivery with strategic influence across engagements. Compensation / Benefits * Design and build AI-enabled solutions inside a client environment (agents, retrieval/RAG pipelines, automation workflows) * Set and own standards for AI production practices (evaluation, guardrails, observability, reliability, security, cost/performance) across multiple engagements * Mentor and manage Engineering Managers and their teams across client engagements * Architect AI capability roadmaps across multiple workstreams or domains * Engage client stakeholders (CISO, resilience and GRC leadership) to prioritize automation for audit/compliance * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and operation of production AI solutions, including troubleshooting * Own technical solutioning during pursuits (POCs, demos, estimates, pricing) across opportunities * Enable clients at scale with workshops, adoption planning, and training curricula * Oversee delivery scope, timelines, quality, and customer satisfaction; drive continuous improvement * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to practice capability development Tasks * 12-15+ years of hands-on software engineering experience * 6+ years translating requirements into target architectures (REST APIs, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP with containers and CI/CD * 3+ years designing, building, deploying generative AI/LLM solutions in production * Experience owning AI production engineering standards across engagements * 3+ years leading and developing engineering teams including managers * Experience architecting AI-enabled solutions across multiple workstreams * Experience contributing to practice capability, hiring, training or reusable IP * Experience enabling client workshops, demonstrations, and adoption planning * Ability to travel 25-50% Key requirements * Discretionary annual incentive program * Travel opportunities (25-50% on average) * Reasonable accommodations available

Requirements

a AI capability roadmaps across multiple workstreams or domains * Engage client stakeholders (CISO, resilience and GRC leadership) to prioritize automation for audit/compliance * Translate client needs into production-grade AI solutions for resilience use cases * Lead hands-on design, integration, deployment, and operation of production AI solutions, including troubleshooting * Own technical solutioning during pursuits (POCs, demos, estimates, pricing) across opportunities * Enable clients at scale with workshops, adoption planning, and training curricula * Oversee delivery scope, timelines, quality, and customer satisfaction; drive continuous improvement * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to practice capability development Tasks * 12-15+ years of hands-on software engineering experience * 6+ years translating requirements into target architectures (REST APIs, aaaaaaaaaaa FDE event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP with containers and CI/CD * 3+ years designing, building, deploying generative AI/LLM solutions in production * Experience owning AI production engineering standards across engagements * 3+ years leading and developing engineering teams including managers * Experience architecting AI-enabled solutions across multiple workstreams * Experience contributing to practice capability, hiring, training or reusable IP * Experience enabling client workshops, demonstrations, and adoption planning * Ability to travel 25-50% Key requirements * Discretionary annual incentive program * Travel opportunities (25-50% on average) * Reasonable accommodations available

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