Required Skills & Experience
5-10+ years of Solution Architecture / Enterprise Architecture experience. Strong experience architecting and scaling large, distributed, mission-critical platforms. Strong understanding of cloud/hybrid infrastructure, APIs, microservices, and event-driven architecture. Experience with incident management, SRE, observability, reliability, and production operations. Ability to assess an existing platform and create both a current-state and future-state architecture/roadmap. Experience with automation and workflow orchestration platforms.
Nice to Have Skills & Experience
Hands-on AI/ML or GenAI experience, particularly:
Agentic AI / AI agents LLMs RAG Prompt engineering AI governance/model evaluation AI-powered operational workflows Cutover experience or experience with comparable incident/remediation automation platforms. Previous system administration / infrastructure background, especially Unix/Linux, networking, or platform engineering. Experience training/fine-tuning models or integrating AI into enterprise production environments. CI/CD and broader infrastructure automation experience.
Job Description
Insight Global is seeking a Solutions Architect in Charlotte, NC for one of our largest financial customers. This individual is responsibility for assessing the current Cutover platform, identify scalability and operational bottlenecks, and define a next-generation architecture for automated incident detection, diagnosis, remediation, and operational orchestration. The individual should combine deep architecture expertise with practical knowledge of AI/ML technologies, large-scale production operations, and emerging automation platforms. The role would support the continued evolution of Cutover, which is already being positioned as a strategic automation platform within multiple business units and has ongoing work around integration scalability, workload isolation, and automation expansion.
Responsibilities include:
Assess and document the current Cutover architecture, integrations, infrastructure, APIs, databases, queues, workers, and data flows. Identify scalability, performance, resiliency, and operational bottlenecks. Evaluate Cutover against other incident resolution and automation platforms/tools in the market. Partner with the SRE/platform teams to understand how incidents are currently detected and resolved.
Help connect an existing AI production-log analysis capability with Cutover:
AI analyzes system/network/production logs and flags abnormal behavior or incidents. AI recommends a known resolution based on historical patterns. Cutover provides the operational tool/workflow needed to execute that resolution. Initially maintain a human-in-the-loop model, where AI recommends the fix and a human approves/executes it. Help establish the architecture and supporting data needed to eventually justify more autonomous remediation. Define the future-state architecture and multi-year roadmap around agentic AI, AIOps, event-driven automation, RAG/LLMs, autonomous remediation, and self-healing platforms