Top Remote Software Engineer Jobs in Charlotte, NC

The role involves designing, developing, and maintaining software applications. Collaboration with cross-functional teams is expected, alongside optimizing existing systems.

Work as a Python development intern building applications and APIs, processing and analyzing data, working with databases and data pipelines, contributing to system architecture, writing clean documented code, and collaborating with the team. Strong emphasis on backend development, SQL, ORMs, and REST API design with potential conversion to full-time.

Lead design, build, test, and deliver Workday integrations across a multi-system higher education environment. Own integration strategy, implement EIBs/Core Connectors/Studio/APIs, coordinate testing and cutovers, ensure FERPA-compliant data security, and partner with vendors and IT for documentation and operational handoff.

Lead Workday configuration and development across modules; design BPF workflows; build calculated fields, condition rules, and custom objects; define security roles; support testing, deployment, and post-production stabilization; document configurations and ensure Higher Ed governance compliance.

Lead architectural vision and delivery for complex, scalable SaaS systems. Design cloud-native distributed systems using Docker and Kubernetes, develop foundational abstractions, reduce technical debt, and drive engineering best practices. Partner with Product, Design, and Engineering leadership, mentor senior engineers, and contribute to hiring. Apply deep C# and .NET expertise, performance analysis, debugging, and AI-assisted development, including production LLM integrations.

The Head of Engineering will drive technical direction, develop product architecture, and eventually lead the engineering team while coding and building AI systems.

Build and own the technical roadmap: design AI-first interfaces and APIs, architect scalable ETL pipelines, develop data models for ML features, ship autonomous B2B workflows (PO generation, vendor sync, schedule optimizations), and establish engineering standards, CI/CD, and mentoring.

Develop and maintain full-stack applications using Vue 3, Nuxt, JavaScript, Node.js, Firebase, Firestore, and Google Cloud Platform. Build APIs, microservices, integrations with AI and marketing platforms, payment systems, and cloud services. Troubleshoot UI, database, deployment, and API issues; write tests; and collaborate remotely with the CTO and development team. This is a part-time, equity-based startup opportunity requiring approximately 20 hours weekly.

Develop and operate authentication, authorization, and identity-provider services for APIs, customer products, and internal tools. Build Go backend services, gRPC/REST APIs, shared libraries, and React/TypeScript interfaces, with occasional Java work. Own services end to end, including data modeling, deployments, monitoring, troubleshooting, integrations, testing, incident response, and on-call support.

Leads the technical vision, architecture, and execution of AI performance, framework, benchmarking, and developer-productivity initiatives. Drives cross-team architecture, resolves complex systems trade-offs, mentors technical leaders, and contributes hands-on through prototyping, implementation, reviews, debugging, observability, and automation. Delivers measurable improvements in model onboarding speed, runtime performance, reliability, hardware utilization, and Azure capacity efficiency across models, frameworks, compilers, runtimes, systems, services, and hardware.

Build and operate Linux and Kubernetes infrastructure for Azure Front Door’s globally distributed edge fleet. Design, implement, validate, and deploy platform capabilities; optimize performance, reliability, scalability, security, and operations; investigate production issues; develop automation and engineering tools; and provide technical guidance through reviews and knowledge sharing.

Builds AI and LLM observability capabilities across data ingestion, infrastructure, analysis, and product visualizations. The role develops systems surfacing cost, token usage, errors, and anomalies; contributes to data models; collaborates with product and design; and ships customer-facing SaaS features. Engineers participate in on-call rotation, experimentation, and fast feedback cycles, with opportunities to work on production LLM and agent-powered features.

Build and own end-to-end AI observability capabilities, including data ingestion, infrastructure, data models, and product visualizations. Develop systems that surface cost, token usage, errors, and anomalies across AI agents. Collaborate with product and design, ship customer-facing SaaS features, guide best practices, and iterate through experimentation. Participate in an on-call rotation after approximately 90 days.