Top Tech Jobs & Startup Jobs in Charlotte, NC

Design and implement cloud services for standardization and optimization, enhance customer experience through Contact Center and Voice Bot integration, and apply DevSecOps in a collaborative environment.

The Lead AI Data Engineer designs and optimizes ETL/ELT pipelines, mentors team members, collaborates on data models, and implements best practices in data governance and security.

Design and drive end-to-end, AI-first digital solutions and reference architectures across cloud, APIs, microservices, and front-end platforms. Provide technical leadership to agile teams, ensure security and cost-conscious modernizations, and align technology strategy with business goals.

The Senior Cloud Engineer will design, support, and automate cloud database solutions using IaC tools. Responsibilities include collaborating with teams, managing CI/CD workflows, automating monitoring, and ensuring database environments are efficient and secure.

Design, develop, and deliver BI dashboards and analytic capabilities for Global Specialty. Drive roadmap execution, translate stakeholder feedback, troubleshoot data issues, and partner across IT and BI teams to promote adoption of data and GenAI solutions.

Lead and mentor a software engineering team to deliver innovative solutions that enhance the claimant experience, ensuring high-quality products and continuous improvement.

Lead development and optimization of ETL pipelines and data architecture, oversee data governance, and integrate AI/ML models for analytics in a cloud environment.

The Senior IT Engineer will lead full stack development projects focused on AWS, architecting APIs, mentoring junior engineers, and ensuring application performance and security.

The role involves gathering and analyzing business data requirements, mentoring analysts, maintaining data documentation, and facilitating communication between business and IT stakeholders.

Design, build, and scale cloud-native backend services for automated document ingestion, classification, extraction, and validation. Ensure performance, reliability, observability, and cost efficiency. Contribute to CI/CD, infrastructure-as-code, system design, code reviews, documentation, and cross-functional collaboration to deliver enterprise-grade Intelligent Document Processing solutions.