Top Remote Entry Level Software Engineer Jobs in CO

Build, test, ship, and operate production backend features with minimal guidance. Design APIs, background jobs, integrations, data models, migrations, and bounded services while maintaining security, performance, observability, and reliability. Review code, improve automated testing, investigate production issues, address technical debt, participate in operational support, and collaborate asynchronously with product, frontend, infrastructure, and security teams. Use AI coding tools responsibly by validating and correcting generated output.

Lead the technical direction of Zocdoc’s patient acquisition platform, building scalable APIs, microservices, AWS infrastructure, and React experiences. Improve SEO, page speed, system reliability, and patient-facing data access. Collaborate with Product, Design, and Marketing, integrate third-party data and Contentful, apply LLM technology, promote engineering excellence, mentor engineers, and drive AI-focused innovation across distributed teams.

Lead Affirm’s Resilience Engineering team, defining strategy and building platforms for safe production load testing and chaos engineering. Manage engineers, establish safeguards such as isolation, approval workflows, rollback, observability, and auditability, and partner across infrastructure, security, and product teams to improve reliability. Drive adoption of resilience practices, identify distributed-system weaknesses, and guide monitoring, alerting, and incident response for production experiments.

As an Outcome Engineer, you will architect multi-agent systems, implement automated governance, and build evaluation frameworks to enhance AI-powered workflows.

The Quantitative Developer will assist with client onboarding, support, implement and maintain new functionality for portfolio compliance, and improve team documentation.

Own and evolve Argo Workflows and Argo Events, make major architectural decisions, and build Pipekit’s enterprise control-plane product. The role includes shaping the roadmap, shipping customer-focused features, engaging with open-source contributors and customers, participating in an on-call rotation, and speaking at cloud-native conferences. Candidates should have strong statically typed programming skills, Kubernetes expertise, production-systems experience, excellent written communication, and a self-directed, customer-focused approach.

Develop and maintain backend services and RESTful APIs using C# and .NET. Design and optimize MySQL schemas and queries, troubleshoot production and staging issues, improve performance and scalability, document architecture, and uphold code quality and security. Collaborate with cross-functional teams in a fully remote environment while contributing to development best practices and continuous improvement.

Own significant areas of PayBox end-to-end, from problem definition through production and iteration. Build AI-interface payment and peer-to-peer transfer experiences, integrations across AI platforms, and infrastructure for applications and plugins. Partner with Product, improve onboarding and UX, make pragmatic architectural decisions, and operate autonomously in an ambiguous, fast-moving environment. The role emphasizes strong systems thinking, product judgment, thoroughness, and extensive but accountable use of AI.

Build full-stack features for search, browsing, content curation, governance, and student exploration across education products. Develop backend services using databases, datastores, messaging, and cloud infrastructure, while building accessible TypeScript and React frontends. Write unit, component, and contract tests and add observability through traces, metrics, and logs. Work independently with distributed teams and help adopt AI-first development through multi-agent orchestration and formal engineering constraints.

Build and operate AI agent systems with customer engineering teams, helping move prototypes into reliable production systems. Design agents, improve evaluations, monitoring, scaling, and reliability, and train customers on the Mastra framework. Translate recurring customer challenges into open-source framework improvements, fix performance issues, ship new primitives, improve code quality, and influence the product roadmap through production insights.