Top Remote C# Jobs in Atlanta, GA

Develop and deploy customer-focused web, mobile, and backend applications across the full software stack. Design major features, contribute to architecture decisions, conduct code reviews, and ensure secure, high-quality implementations. Collaborate with stakeholders and cross-functional teams using Agile and SDLC practices. Manage version control, CI/CD, environments, and releases; maintain automated test coverage and perform root-cause analysis. Build and optimize relational data solutions using SQL Server, including complex queries, stored procedures, and performance tuning.

Designs and builds backend services, internal libraries, cloud-native applications, and AI agent workflows using .NET, Azure, and Semantic Kernel. Develops reliable, observable enterprise software, contributes to architecture and design documentation, performs code reviews, mentors engineers, and improves performance, security, developer experience, and CI/CD practices. May also develop Angular tooling and components.

Lead and mentor the software engineering team responsible for PSA Set Registry, a large-scale consumer web and mobile product. Drive architecture, development, delivery, code quality, release management, production troubleshooting, and technical strategy. Partner with product, design, and business teams to translate requirements into scalable solutions while promoting agile practices, collaboration, continuous learning, and an inclusive engineering culture.

Leads Site Reliability Engineering strategy and a team of SREs supporting mission-critical platforms. Responsibilities include improving reliability, scalability, observability, security, and performance; driving cloud modernization across Azure and AWS; implementing infrastructure automation, SLOs, incident management, governance, and disaster recovery; and mentoring engineers while coordinating cross-functional initiatives across product, platform, security, and business teams.

Design, build, and operate reliable, scalable services across the C+E stack. Automate operations with scripts and CI/CD, use telemetry to detect trends, perform root cause analysis, support dedicated cloud environments, and collaborate across teams to ensure security, compliance, and operational excellence.

Leads architecture and hands-on development of scalable backend systems and APIs supporting real-time applications. Owns the engineering lifecycle, writes high-performance code, establishes testing and reliability practices, resolves production issues, guides technical roadmaps, collaborates cross-functionally, and mentors engineers. The role requires expertise in object-oriented backend development, distributed cloud systems, automated testing, system monitoring, and technical leadership.

Design, implement, and improve Microsoft 365 sovereign cloud services for government customers. Develop and test code to increase availability, reliability, performance, and observability of large-scale distributed systems; build telemetry and automation; troubleshoot production issues; participate in code/design reviews, on-call rotations, and incident response; collaborate with product teams to deploy scalable solutions.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers to translate requirements into technical designs, drive engineering best practices (CI/CD, testing, observability), deliver end-to-end solutions, lead technical workstreams, and apply AI/LLM approaches where appropriate to produce production-ready outcomes.

Design, develop, test, deploy, and operate secure Teams Phone services in sovereign and air-gapped cloud environments. Build scalable distributed systems, improve reliability and observability, participate in on-call support, troubleshoot production incidents, and contribute to automation, CI/CD, documentation, and operational excellence. Collaborate with engineering, product, security, privacy, and SRE teams while using AI tools responsibly throughout the software development lifecycle.

Lead design and build of production-ready cloud and AI systems, prioritize security and reliability, ship solutions quickly using modern engineering practices, collaborate with cross-functional teams, mentor engineers, drive customer adoption, and deliver reusable assets and end-to-end complex deliveries.

Designs and directs development of scalable software systems using AI-assisted engineering practices. Owns architecture, APIs, data models, testing strategy, security, reliability, observability, deployment, and production operations. Decomposes work for AI agents, validates generated code and tests, leads incident response, and coaches engineers on effective AI-enabled development. Requires full-stack experience, modern server-side development, event-driven systems, cloud infrastructure, regulated-data security, and production use of agentic AI.

Leads enterprise software development, platform integrations, custom scripts, and cloud architecture. Manages the software development lifecycle from requirements through deployment, collaborates with stakeholders, mentors engineers, and directly contributes to frontend, backend, and cloud solutions. Oversees third-party enterprise tools, databases, APIs, serverless systems, QA coordination, technical processes, and cross-departmental engineering initiatives.

Drive technical direction and architecture across teams for enterprise retail software. Improve platform reliability and performance, scope customer-facing features, mentor engineers, de-risk large work, and embed AI-native practices (LLMs/agents) into engineering workflows.

Designs, builds, scales, and operates distributed CI/CD services supporting millions of builds, tests, and releases. Develops code for Azure-based infrastructure spanning virtual machines, containers, and custom lab environments. Responsibilities include requirements analysis, architecture and design documentation, estimation, debugging, optimization, operational playbooks, on-call incident response, monitoring, reliability improvements, and mentoring engineers.

Designs and maintains enterprise software, APIs, microservices, databases, ETL pipelines, CI/CD workflows, RPA solutions, and AI/LLM applications. Leads architecture and engineering reviews while implementing secure integrations, data governance, HIPAA/PII compliance, vector search, RAG, agentic workflows, and responsible AI practices. Collaborates with technical, compliance, data, and business stakeholders to move automation and AI solutions from prototypes into production.

Develop and support high-volume, mission-critical web applications across the full software development lifecycle. Build with TypeScript, JavaScript, Next.js, and SQL; deploy and operate applications in Microsoft Azure; use AI-assisted development tools; troubleshoot complex technical issues; make architectural decisions; and mentor other engineers. The role requires multi-tier system development, database optimization, Agile collaboration, and proactive delivery of reliable, high-quality software.

Develop and deliver high-volume enterprise applications across the full software development lifecycle. Design, code, test, debug, optimize SQL solutions, troubleshoot complex issues, contribute to scalable architecture, collaborate with technical and business stakeholders, and mentor other developers. Work independently while participating in Agile development and production implementation.

Design and build Azure Kubernetes Service features and AI-native infrastructure, improve service reliability and developer velocity, automate incident prevention/remediation, integrate AI tools, and operate distributed, containerized systems at cloud scale.

Lead and grow an engineering team that designs, builds, and operates hyperscale distributed systems and cloud-native platform services for Azure. Drive technical strategy, architecture, cross-team initiatives, operational excellence, and stakeholder collaboration to deliver scalable, reliable, secure, and observable infrastructure solutions.

Build and optimize Azure Storage’s hyperscale distributed file system. Responsibilities include designing and implementing storage features, analyzing performance, ensuring availability, security, reliability, and durability, creating technical designs, estimating work, monitoring services on call, and improving observability and operational efficiency at scale.

Lead full-stack .NET development, legacy application modernization, accessibility auditing, and code remediation. Develop accessible web interfaces and PDF reports compliant with WCAG 2.1/2.2 AA, WAI-ARIA, and Section 508. Use C#, ASP.NET Core, JavaScript, Telerik, CSS, Crystal Reports, screen readers, automated scanning tools, and AI-assisted engineering tools. Configure CI/CD pipelines, manage Git workflows, and support testing and release engineering.

Design, develop, and operate distributed services for Azure Storage geo-replication. Improve durability, regional resiliency, failover readiness and disaster recovery. Collaborate across teams, analyze telemetry, diagnose production issues, act as a DRI, and leverage AI-assisted engineering tools to improve productivity and reliability.

Leads the design, implementation, optimization, and support of highly scalable Azure Storage services. Responsibilities include end-to-end performance testing, benchmarking, automation, profiling, bottleneck and root-cause analysis across compute, storage, and networking layers, KPI definition, scaling recommendations, and operational incident response. The role collaborates across teams, drives project and release plans, supports reliable and secure services, and mentors engineers while participating in on-call responsibilities.

Develops and maintains high-quality systems software and microservices for Azure Messaging services, including data storage and replication. Drives product and engineering-process innovation, applies AI to software development, ensures software quality and stability, and uses rigorous development practices including requirements, testing, and efficient coding techniques.

Design and maintain scalable services, APIs, distributed systems, and data pipelines for AI training data infrastructure. Own systems through design, implementation, testing, deployment, and monitoring. Lead architectural decisions, improve reliability and scalability, mentor engineers, and collaborate with AI/ML, product, and data operations teams. Contribute to CI/CD, containerization, DevOps, and cloud deployment practices.