Cyber Senior Manager - Technology Resilience FDE

Experteer Overview In this role you will embed within a client’s environment to design, build, and deploy production-grade AI capabilities using their data and systems, while leading the engineering team and technical roadmap. You will shape AI solutions across multiple engagements, focusing on resilience, disaster recovery, and control automation. You’ll mentor engineers, own solution architecture, and drive adoption of reusable accelerators and capabilities. You’ll trabajar with stakeholders to align AI efforts with audit and resilience goals, delivering impact at scale. Compensation / Benefits * Design and implement AI-enabled solutions inside a client environment using live data and systems * Set and enforce AI production practices including evaluation, guardrails, observability, reliability, security, and cost/performance management * Lead and develop Engineering Managers and teams across client engagements * Architect AI capability roadmaps across multiple workstreams and domains * Engage client stakeholders (CISO, resilience/GRC leaders) to prioritize automation of controls and evidence workflows * Translate client resilience needs into production-grade AI solutions * Lead hands-on design, integration, deployment, and operation with issue resolution * Own technical solutioning during pursuits: demos, PoCs, estimates, and pricing inputs * Own client enablement across engagements: workshops, adoption planning, handoff, training curricula * Manage delivery: scope, timelines, quality, customer satisfaction, continuous improvement * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to practice growth, hiring, and IP Tasks * Bachelor in CS/Engineering/IT or related field, or equivalent experience * 12-15+ years of hands-on software engineering delivering production-grade systems * 7+ years translating business requirements into target-state architectures (REST APIs, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, and version control * 3+ years designing, building, deploying generative AI/LLM solutions (agents, RAG, tool-calling) * 3+ years owning AI production engineering standards across multiple engagements * 3+ years leading and developing engineering teams (Engineering Managers or equivalent) * Experience architecting AI-enabled solutions across multiple workstreams with a coherent roadmap * Experience contributing to practice capability: mentoring, hiring/training, reusable IP * Experience enabling clients at scale: workshops, demonstrations, adoption planning, handoff * Experience creating reusable AI accelerators/tools and scaling adoption * Ability to work independently in a client environment and navigate undocumented workflows * Ability to integrate automation with monitoring, ITSM, or GRC platforms * Willingness to travel 25-50% * Limited immigration sponsorship may be available Key requirements *

_ * Engage client stakeholders (CISO, resilience/GRC leaders) to prioritize automation of controls and evidence workflows * Translate client resilience needs into production-grade AI solutions * Lead hands-on design, integration, deployment, and operation with issue resolution * Own technical solutioning during pursuits: demos, PoCs, estimates, and pricing inputs * Own client enablement across engagements: workshops, adoption planning, handoff, training curricula * Manage delivery: scope, timelines, quality, customer satisfaction, continuous improvement * Create reusable accelerators and scale adoption with documentation and knowledge transfer * Own the technical roadmap across engagements and contribute to practice growth, hiring, and IP Tasks * Bachelor in CS/Engineering/IT or related field, or equivalent experience * 12-15+ years of hands-on software engineering delivering production-grade systems * 7+ years translating business requirements into target-state architectures (REST APIs, microservices, event-driven, or serverless) * 3+ years delivering solutions on AWS, Azure, or GCP including containers, CI/CD, and version control * 3+ years designing, building, deploying generative AI/LLM solutions (agents, RAG, tool-calling) * 3+ years owning AI production engineering standards across multiple engagements * 3+ years leading and developing engineering teams (Engineering Managers or equivalent) * Experience architecting AI-enabled solutions across multiple workstreams with a coherent roadmap * Experience contributing to practice capability: mentoring, hiring/training, reusable IP * Experience enabling clients at scale: workshops, demonstrations, adoption planning, handoff * Experience creating reusable AI accelerators/tools and scaling adoption * Ability to work independently in a client environment and navigate undocumented workflows * Ability to integrate automation with monitoring, ITSM, or GRC platforms * Willingness to travel 25-50% * Limited aaaaaaaa Own sponsorship may be available Key requirements *