Nuclear Promise X

• Design, build, and deploy software solutions impacting nuclear industry projects. • Collaborate with developers and stakeholders to improve workflows and efficiencies. • Support the transition of tools into production with hands-on development. • Troubleshoot, debug, and improve existing applications. • Iterate quickly through feedback and learning processes.

• Design and implement end-to-end AI system architectures. • Develop backend services, APIs, and data pipelines integrating AI models. • Write and maintain Python code leveraging Azure cloud services. • Prepare, structure, and validate training datasets with production constraints. • Contribute to technical discussions and architectural decisions.

• Architect, implement, and maintain secure cloud infrastructure (Azure, AWS, or GCP). • Lead containerization and orchestration efforts using Docker and Kubernetes. • Design, build, and optimize CI/CD pipelines incorporating automated testing. • Develop and maintain infrastructure-as-code (Terraform, ARM, or equivalent). • Establish observability standards using modern monitoring tools. • Own reliability engineering practices including disaster recovery strategies. • Implement secure architecture patterns, IAM controls, secrets management. • Collaborate closely with software engineers to embed DevOps best practices. • Contribute to architectural decisions and define cloud platform standards. • Lead post-incident sessions for root-cause analysis when needed.

• Own the architecture and technical direction of critical .NET systems across application and infrastructure layers. • Design and deliver cloud-native, distributed applications that power mission-critical nuclear industry workflows. • Architect for scalability, observability, and resilience — ensuring systems perform under real-world operational constraints. • Lead complex initiatives spanning application code, data layers, CI/CD pipelines, and deployment environments. • Partner with product and leadership to translate business objectives into scalable technical strategy. • Raise the engineering bar through rigorous code reviews, best practices, and operational excellence. • Proactively identify and eliminate systemic bottlenecks across code, pipelines, and environments. • Shape our technical roadmap across platform, reliability, and performance domains.

• The development of an application from scratch, and building on top of an existing application, to set our products up to scale across multiple clients in the nuclear industry. • The implementation of new features and integrations to enhance the application’s capabilities. • Partner with engineers, designers, and analysts to solve complex technical challenges and improve application performance. • Proactively identify and improve code quality, system performance, and scalability to make the platform more reliable and maintainable. • Translate complex technical challenges into actionable plans, ensuring the platform continues to support safer, faster, and more cost-effective nuclear operations.

• Design and develop AI-powered solutions using Microsoft Azure services, including OpenAI, Cognitive Search, Vision, Document Intelligence, and Cosmos DB for vector storage. • Build and iterate on retrieval-augmented generation (RAG) pipelines and knowledge-grounded architectures, including GraphRAG and emerging techniques like OmniRAG. • Rapidly prototype AI applications tailored to specific client needs, such as document digitization, data vectorization, and content generation workflows. • Contribute to the architecture and implementation of advanced AI systems, including agent-based orchestration and integration with modern APIs and platforms. • Prepare and structure training data, including labeled inputs for both text and image-based models, with a focus on production readiness and model performance. • Evaluate and adopt new tools and frameworks based on AI/ML advancements, ensuring that implementations are stable and scalable. • Collaborate across teams to deliver high-impact, cloud-native applications using Python (especially Azure's AI SDK). Exposure to JavaScript/TypeScript or Node.js is considered an asset. • Apply familiarity with engineering documentation and visuals (e.g., diagrams, schematics) to enhance AI-driven workflows where applicable.