Top Tech Jobs & Startup Jobs in Charlotte, NC

Supports actuarial pricing and product strategy for Small Business commercial insurance. Responsibilities include developing rate indications, refining pricing segmentation, updating loss development factors and assumptions, analyzing deductibles and insurance limits factors, monitoring profitability, and supporting class plan rollouts. The role uses SQL, R, Python, Excel, and related tools to improve analytics, partners with underwriting and product teams, presents results to leadership, and mentors junior actuaries.

Architect and build production-grade agentic AI systems and platforms using Google ADK, MCP, LangChain/LangGraph, and AlloyDB. Develop agent harnesses, RAG/GraphRAG pipelines, vector retrieval and memory stores, Terraform-based GCP infrastructure, CI/CD for model deployments, and enterprise security and governance for sessioned agent interactions.

Lead design and delivery of scalable, secure software across full stack and cloud. Collaborate with product and architecture teams, mentor engineers, drive best practices, integrate AI-assisted tools, and participate in the full SDLC to ensure system stability and performance.

Lead development and maintenance of workers' compensation pricing methodologies and tools. Update model parameters, drive pricing initiatives, collaborate with underwriting/product/data science/IT, provide profitability analyses, and support implementation to improve accuracy, segmentation, and profitable growth across business segments.

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.

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.