Cyber Senior Manager - Technology Resilience FDE
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
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
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Apply on us.experteer.comGood distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Navigating the AI Shift
Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production
Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence
Stephan Gillich - Bringing AI Everywhere