Top Tech Jobs & Startup Jobs in Charlotte, NC

Leads enterprise data engineering, AI engineering, and data management teams. Owns strategy, roadmaps, and delivery for governed data products, cloud-native platforms, lakehouse architectures, semantic intelligence, and AI-enabled analytics. Drives AWS modernization, DataOps, MLOps, governance, security, reliability, responsible AI, and platform adoption while partnering with business and technology executives. Builds organizational capability, recruits talent, and translates complex data and AI investments into measurable business outcomes.

Design and deploy AI/ML solutions, including agentic AI systems, multi-agent LLM applications, enterprise knowledge systems, and predictive models. Partner with stakeholders to solve high-value business problems, establish evaluation frameworks, and implement monitoring, guardrails, explainability, and responsible AI practices. Collaborate with engineering teams on scalable production deployment, advise on AI strategy, and mentor colleagues.

Leads Vanguard’s tokenization strategy by identifying and prioritizing use cases, evaluating market, regulatory, operational, and technical factors, and advising senior leadership. Partners with business, technology, legal, compliance, risk, product, and engineering teams to develop adoption roadmaps and validate opportunities. Monitors industry and regulatory trends, evaluates vendors and partnerships, represents Vanguard in industry forums, communicates strategic recommendations, and mentors colleagues on tokenization and digital assets.

Designs secure, scalable, and responsible AI architectures for LLM applications, RAG, agentic workflows, APIs, and enterprise data integration. Defines reusable patterns, deployment approaches, governance controls, evaluation practices, and observability standards. Partners with engineering, product, data, risk, security, and architecture teams; reviews solutions and code, optimizes reliability and cost, mentors technical teams, and enables production AI adoption across the enterprise.

Design, develop, and support cloud-based applications, APIs, integrations, and backend systems. Translate business requirements into scalable technical solutions, integrate Workday, ServiceNow CMDB, Jira, and Genetec, and migrate security technologies to AWS-native services. Manage deployments across development, test, and production environments, apply enterprise security and documentation standards, optimize performance, and collaborate with business, technology, and vendor teams.

Leads business requirements, process documentation, governance artifacts, operational playbooks, and readiness activities for debit card and money movement initiatives. Coordinates stakeholders across Product, Operations, Risk, Compliance, Legal, Technology, vendors, and program leadership. Tracks dependencies, decisions, and deliverables; supports feature prioritization, vendor onboarding, contract requirements, launch readiness, and transition into ongoing operations.

Leads cross-functional strategy and execution for money movement initiatives across Product, Operations, Fraud, Risk, Compliance, Technology, and Client Experience. Responsibilities include requirements gathering, dependency and risk management, executive reporting, roadmap alignment, policy modernization, fraud-control integration, vendor analysis, and implementation readiness. The role improves funding, transfer, withdrawal, and payment experiences while balancing client outcomes, operational efficiency, and risk mitigation.

Lead data governance and management initiatives: define and implement data quality, metadata, and lineage controls; translate governance strategy into measurable plans; partner with stakeholders to remediate issues, track metrics, and deliver outcomes; support modern data platforms and AI readiness; present results to senior leadership.

Lead the launch and scaling of Vanguard's Debit Card program within the mobile app. Define product features and implementation plans, drive SDK integrations and technical partnerships, create unified in-app card controls, collaborate with cross-functional teams, resolve production issues, use qualitative and quantitative analysis to improve user experience, support messaging and customer outreach, and participate in business planning and special projects.

Partner with business stakeholders to identify high-value AI use cases and deliver agentic AI and LLM solutions. Architect multi-agent and tool-augmented LLM systems, ensure scalability, security, explainability, and governance. Collaborate with engineering to deploy production-grade solutions, implement evaluation/monitoring and guardrails, and act as an enterprise AI advisor while mentoring peers and contributing AI best practices.