We are seeking a highly skilled Solution Architect focused on Digital, AI & Data Transformation. Architect will lead the design, development, and implementation of next-generation Optum Bank's Digital, data and AI systems. This role combines deep hands-on engineering with strategic architecture, focusing on modern data transformation pipelines, small language models (SLMs), AI frameworks, and AI/ML solutions such as fraud detection, lending underwriting models, Operational Agents, and others.

AI & Data ArchitectureArchitect and lead end-to-end data transformation pipelines, including ingestion, normalization, quality, feature engineering, and real-time processingDesign and implement Small Language Models (SLMs) optimized for domain-specific tasks such as customer interactions, document understanding, or process automationBuild and maintain AI frameworks enabling scalable training, inference, experiment tracking, observability, and model governanceArchitect and deploy AI Agents capable of orchestration, reasoning, planning, and workflow automation across enterprise systemsDevelop and operationalize AI/ML models including:Fraud detection (transaction scoring, anomaly detection)Lending underwriting (risk modeling, creditworthiness, scoring pipelines)Personalization, recommendation, NLP, forecasting, and moreTechnical Leadership & Hands-On EngineeringLead technical design sessions, conduct POCs, and build reference architectures and reusable frameworksWrite high-quality, production-grade code in languages such as Python, Java, Scala, or TypeScriptPartners with data engineering teams to optimize Datalake/Lakehouse house, distributed computing, and feature engineering architecturesEvaluate emerging AI/ML technologies and drive adoption of best-fit solutionsAI-Driven Developer ProductivityLeverage Claude Code, GitHub Copilot, and similar AI-assisted development tools to:Increase developer velocityImprove code quality and consistencyAutomate documentation, testing, and code review workflowsReduce time-to-market for complex transformation initiativesEvangelize AI-powered engineering patterns and train teams on effective usageApplication Modernization & TransformationGuide modernization of legacy systems into cloud-native, AI-native applicationsDefine patterns for integrating AI agents, LLMs, and SLMs into operational applications and microservicesCollaborate with platform teams to ensure efficient infrastructure, MLOps, CI/CD, and model deployment workflowsGovernance, Risk & ComplianceEnsure responsible AI practices including fairness, explainability, model monitoring, ethics, and regulatory alignment (eg, lending compliance)Implement robust evaluation and drift detection frameworksCross-Functional CollaborationInfluence senior leaders, product teams, and engineering stakeholders on AI strategy and roadmapAct as technical mentor and thought leader across AI and data domains