• The Mechanical Analysis Engineer is responsible for the delivery of high-quality engineering analyses • Develop creative solutions and reduce analysis complexity to create accurate and effective solutions for complex engineering problems • Analyze primary plant structures to develop loads and response characteristics • Qualify RPV or Reactor Internals repairs or replacement components considering static, dynamic, thermal, and flow-induced loads • Engage customers to define scope, review results, and discuss technical risks • Work with the technical leader to establish an effective work plan, including time estimates, schedule estimates, requirements, and work processes • Apply vibration and acoustics first principle analytical methods (e.g., strouhal calculations for acoustic resonance, structural natural frequency calculation based on mass and stiffness, etc.) • Development of numerical acoustic models of the reactor internals, reactor steam dome, and reactor systems (e.g., main steam line and attached components) utilizing ANSYS finite element software or other similar numerical methods • Translation and manipulation of data between the time and frequency domain including (e.g., calculation of power spectral density (PSD plots) from time domain data) for development of bias and uncertainty between calculated and measured response • Support test planning and execution for validation of GVH designs • Provide clear and complete analysis documentation in accordance with GE engineering procedures • Analysis results typically provided in an engineering report for use by external customers • Ability to present analysis results in a clear, organized and concise manner • Manage time effectively to provide quality deliverables within the expected project timeline • Communicate effectively to leadership the status of work activities • Effectively manage multiple priorities

• Developing innovative technical solutions to improve Customer Support efficiency and performance • Working closely with members of Support Leadership to discover and design opportunities for tooling improvements • Understanding Support and customer experiences in order to identify opportunities for improvement • Working closely with other Software Engineers on projects and goals

• Hands-on Data & AI Solutions for Operations Support • Lead and contribute to high-impact data and AI initiatives that improve operations support outcomes, including real-time incident enrichment, automated root‑cause analysis, predictive alerting, ticket clustering and auto-triage, change risk scoring, knowledge mining, and intelligent runbooks. • Design and deliver scalable AI-enabled features embedded into operations support platforms such as ServiceNow, Jira Service Management, monitoring/observability tools, and ITSM systems. • Ensure all solutions meet strict operational SLAs for reliability, low latency, auditability, explainability, and zero-downtime deployment. • Stay up to date with emerging AIOps tools, research, and trends, and apply them to enhance operations support. • Lead the architecture, development, and continuous improvement of internal AIOps platforms and reusable components supporting operations teams. • Integrate AIOps tools with ITSM systems, observability platforms (Prometheus, Grafana, ELK, Dynatrace, Splunk), ticketing systems, and automation frameworks. • Serve as the principal AI technical authority for operations support transformation programs across service operations, NOC, support desks, infrastructure operations, and reliability engineering. • Build, mentor, and lead a high-performing squad of AIOps specialists focused on measurable operations support improvements.

• Design and evolve Node.js / NestJS services powering systems that operate at scale • Take architectural decisions that balance scale, cost, and long-term maintainability • Build well-typed, thoughtful REST contracts for high volume flows • Think in versioning, backward compatibility, and clean boundaries • Model and optimize MongoDB / Firestore schemas for high read/write workloads • Design atomic updates and consistency strategies for distributed systems • Implement queues, caching layers, and rate limiting to handle burst traffic gracefully • Design for failure modes before they happen • Ship modular Vue 3 UIs that efficiently consume APIs • Optimize realtime updates and state management (Pinia) • Improve Core Web Vitals and perceived performance • Instrument logs, metrics, traces, and alerts • Participate in on-call • Debug real production issues • Drive post-mortems to meaningful closure (not just documents) • Review code thoughtfully • Support junior engineers • Raise engineering standards across the team