SummaryCapital Community Bank is seeking a highly motivated AI & Process Automation Engineer to serve as the Bank’s first dedicated AI resource. This role is responsible for identifying, designing, building, and deploying AI-driven solutions and lightweight software tools that improve operational efficiency across the organization.The position will embed directly with business teams, starting in Compliance, then rotating through Operations, Lending, Risk, Finance, and other areas, to discover automation opportunities and deliver measurable results. This role bridges business units, IT, and compliance to ensure AI is implemented responsibly, securely, and effectively.Key ResponsibilitiesAI Opportunity Identification & DevelopmentPartner with business units across the Bank to identify high-impact problems that can be solved using AI, automation, and intelligent tools.Translate business needs into structured Project Charters that define estimated value, delivery timelines, and measurable success criteria.Design, build, and deploy AI-powered solutions, including process automations, data extraction tools, and workflow optimizations, using both custom code, AI coding tools and existing platforms.Develop lightweight, user-friendly software interfaces that enable non-technical staff to adopt and effectively use deployed solutions.Continuously evaluate and improve deployed solutions based on performance data and user feedback.AI Governance & Risk ManagementMaintain an inventory of AI tools, use cases, and data access points across the organization.Ensure all AI implementations comply with internal policies, banking regulations, data privacy requirements, and the Bank’s risk management framework.Collaborate with IT, Security, and Compliance to assess risks and approve new AI use cases prior to deployment.Document data flows, system interactions, and AI decision-making processes for audit and regulatory readiness.Documentation & Process StandardizationCreate and maintain comprehensive documentation for AI workflows, configurations, and business processes.Develop SOPs, training materials, and user guides for all deployed AI tools.Establish repeatable, scalable processes and frameworks for future AI implementations.Training & AdoptionProvide hands-on training and support to end users on AI tools and best practices.Serve as the Bank’s internal subject matter expert on AI, automation, and emerging technology.Drive adoption through education, workshops, and ongoing support; help build an innovation-forward culture.Performance Tracking & ReportingDefine and track KPIs to measure the impact of AI initiatives, including time savings, cost reduction, efficiency gains, and adoption rates.Report on AI usage, adoption, and ROI to senior leadership on a regular cadence.Continuously identify opportunities for improvement, expansion, and new project pipeline development.QualificationsRequired:Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related field, preferred.Strong programming skills in Python and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, or similar).Ability to design and build functional, user-facing software applications (web or desktop) with clean, intuitive interfaces.Experience with generative AI tools and APIs (e.g., OpenAI, Anthropic, open-source LLMs).Strong documentation and process design skills.Understanding of data sensitivity, security, and compliance principles.Excellent communication skills with the ability to translate complex technical concepts into clear, business-friendly language.Self-directed work style with the ability to manage multiple projects and stakeholders simultaneously.Must pass a background check, credit check, and drug screen.Preferred:Experience in banking, financial services, fintech, or other regulated industries.Familiarity with front-end development frameworks (React, Vue, or similar) for building lightweight internal tools.Working knowledge of SQL, databases, and data pipeline design.Understanding of compliance and regulatory technology concepts (BSA/AML, KYC, TILA, UDAAP, FFIEC guidelines).Familiarity with data governance, risk management, or compliance frameworks.Experience deploying solutions in cloud environments (AWS, Azure, or GCP).Experience with workflow automation tools or scripting (Power Automate, Zapier, etc.).Key Success MetricsNumber and quality of AI solutions successfully deployed and adopted.Time and cost savings generated by deployed tools, as documented in Project Charters.AI adoption rates across departments.Compliance adherence, zero data incidents related to AI usage.Documentation completeness and audit readiness.Stakeholder satisfaction with delivered solutions.