Top Tech Jobs & Startup Jobs in Charlotte, NC

Develop and maintain automated testing frameworks and suites for UI, API, integration, database, functional, regression, and end-to-end testing. Create test strategies, plans, cases, and scenarios; validate system controls and compliance requirements; manage defects; analyze quality metrics; and support release and production validation. Collaborate with product, business analysis, development, and DevOps teams throughout the software development lifecycle.

Develop responsive, accessible, and performant full-stack user interfaces using React or Vue.js, JavaScript or TypeScript, and Java backends. Responsibilities include component architecture, state management, REST API integration, CSS implementation, frontend tooling, UI testing, browser performance optimization, and CI/CD deployment processes. The developer will collaborate with backend teams and work within an Agile environment.

Designs and leads large-scale software architecture across cloud, DevOps, mobile infrastructure, integration platforms, and enterprise automation. The role owns technical specifications, design reviews, codebase and roadmap modernization, system scalability, security, observability, release automation, and AI-assisted engineering adoption. It influences product strategy, investment decisions, technical direction, and measurable business outcomes while leading distributed engineering initiatives across technology domains.

Design, build, and maintain scalable batch and streaming data pipelines using Python, SQL, Kafka, and GCP. Develop REST and GraphQL data services, CI/CD automation, observability, and data-quality frameworks. Integrate ML and NLP models into production workflows, including continuous retraining and real-time inference. Support structured and unstructured healthcare datasets, distributed systems, microservices, and reliable data infrastructure while collaborating with data science and MLOps teams.

Develop and maintain scalable Java and Spring Boot backend applications, microservices, and RESTful APIs. Responsibilities include database integration, code reviews, performance optimization, production troubleshooting, testing, CI/CD, cloud deployment, and collaboration with product, QA, and DevOps teams.

Analyzes data sources and information management systems to identify root causes of data governance issues. Partners with data owners, clients, vendors, and data architects to resolve issues, establish governance standards, define data requirements, and integrate governance testing into ETL processes. Develops audit baselines, governance metrics, reports, policies, and continuous improvement initiatives while communicating governance benefits to stakeholders.

Lead iOS and Android mobile application development. The job description does not provide further responsibilities, qualifications, or technical details. Compensation ranges from $52,000 to $182,000 annually, with benefits available to full-time employees. Independent contractor arrangements are also available.

Leads the architecture, design, development, and delivery of enterprise-scale Vue.js and Nuxt.js applications. Responsibilities include front-end standards, solution design, SSR and SSG implementation, API integration, code reviews, mentoring, stakeholder collaboration, sprint and release planning, automated testing, CI/CD, performance optimization, accessibility, SEO, and security compliance.

Develop and maintain scalable Java and Spring Boot backend applications and REST APIs. Optimize CPU, memory, and overall application performance; identify bottlenecks; resolve production issues; and contribute to architecture, code reviews, reliability, and scalability. The role also involves Node.js or Python FastAPI services, cross-functional collaboration, and potential work with GraphQL, generative AI, cloud platforms, containers, CI/CD, and monitoring tools.

Design and implement enterprise AI architectures spanning GenAI, machine learning, RAG, agentic workflows, data pipelines, APIs, and production deployments. Build Python prototypes and AI services, define governance and evaluation frameworks, integrate models with enterprise platforms, and guide engineering teams through implementation. The role requires hands-on expertise with LLM applications, orchestration frameworks, model lifecycle management, monitoring, security, and scalable production AI systems, preferably in financial services.