• Serve as the technical lead for AI application development within the AI Foundry, setting standards for code quality, architecture, and delivery • Lead by doing: design and implement core AI application components, critical services, and integration layers • Mentor AI engineers; raise the bar on engineering rigor and AI-specific best practices • Establish quality thresholds and release criteria (accuracy, latency, reliability, cost, and user trust) • Design safeguards and “safe failure modes”: fallback behaviors, confidence thresholds, user controls, content filtering, and transparency patterns • Build AI-powered product capabilities end-to-end (service + workflow integration + instrumentation), including LLM-enabled workflows, RAG, summarization, classification, and automation patterns • Build and maintain shared libraries/components for AI application development (prompt/tooling patterns, service templates, evaluation utilities, safety layers) • Own technical readiness for production: reliability, observability, performance tuning, and incident response preparedness • Collaborate with platform Engineering and DevOps to ensure CI/CD and environment consistency, scaling strategies, cost controls for inference and secrets management and secure data handling • Partner tightly with AI product builders and workflow Product owners to translate validated prototypes into production implementations • Collaborate with core engineering teams to integrate AI capabilities into CentralReach’s main platforms • Identify and prioritize foundational investments that increase delivery velocity and reduce long-term maintenance: reusable components, platform primitives, and standardized patterns • Evaluate build vs. buy decisions for AI tooling and recommend approaches aligned to CR constraints • Stay current with AI application engineering practices and help translate emerging techniques into safe, valuable product capabilities