Top Tech Jobs & Startup Jobs in Charlotte, NC

Senior technical leader owning end-to-end platform strategy, architecture, and delivery for Digital Enablement. Hands-on coding, driving modernization to cloud-native, API/microservices/event-driven designs, embedding AI-first practices, ensuring reliability, observability, and engineering excellence while mentoring teams and influencing cross-functional stakeholders.

The AVP, Software Engineering Lead oversees the engineering strategy focusing on AI-first approaches, driving modernization and efficiency in software development while ensuring governance and risk management.

Perform reserve studies for specialty financial lines (D&O, E&O, Cyber, EPL, Fidelity), monitor portfolio performance, develop reserving diagnostics and tools, partner with Claims and Pricing to evaluate reserve adequacy, analyze emerging claim trends and significant losses, and drive improvements in data quality, monitoring, and actuarial processes while translating analyses into actionable business insights.

Perform actuarial pricing and reserving tasks for Financial Lines, including rate development, price monitoring, loss ratio planning, profitability studies, reserve analyses, and rate filing support. Partner with Underwriting, Finance, Claims, and IT to improve pricing methodologies, build monitoring tools, analyze trends, and present recommendations to business partners.

Lead a small actuarial team supporting Middle & Large Property lines, owning loss ratio planning, catastrophe risk budgeting, monitoring loss and premium trends, supporting reinsurance, producing pricing and financial materials for leadership, and delivering ad hoc and emerging-risk analyses to improve portfolio performance.

Design, build, and operate enterprise AI/ML platform capabilities (AIOps/MLOps/LLMOps). Develop GenAI features, experiment with models and services, and architect end-to-end solutions. Collaborate with data, cloud, and business teams, drive engineering execution, promote best practices, and mentor engineers. Ensure platform reliability, monitoring, and scalable deployments across cloud environments.

Design and build production-scale data pipelines, orchestration, and integrations on GCP to enable metadata-driven governance, lineage, automation, and AI-enabled workflows. Implement secure, observable, cost-efficient cloud data solutions, embed governance into engineering workflows, and drive CI/CD, testing, monitoring, and platform engineering best practices.

Lead enterprise data platform engineering strategy and teams to build, modernize, and operate scalable, secure data platforms, analytics, AI-ready capabilities, and Third-Party Data enablement. Drive platform architecture, cloud modernization, integration, governance, observability, and operational excellence while partnering with stakeholders to deliver analytics, BI, and AI-enabling solutions and mentor engineering leaders across a global, matrixed organization.

Design, build, and operationalize production-grade AI/Machine Learning solutions and MLOps services. Deploy models and API services to AWS and GCP using CI/CD and IaC, implement workflow automation, monitor post-production performance, research generative/ML techniques, and mentor junior engineers while collaborating with cross-functional data, cloud, and architecture teams.

Lead Applied AI strategy and execution across Employee Benefits and Operations, overseeing ML, generative and agentic AI, RAG, and predictive analytics lifecycles. Drive governance, model risk management, evaluation, deployment, cross-LOB prioritization, talent architecture, and regulatory readiness to improve enrollment, billing, service, and operational efficiency.