Top Remote Entry Level Software Engineer Jobs in Boston, MA

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.

Lead the full software development lifecycle for internal and customer-facing observability systems. Design, build, deploy, support, and optimize scalable distributed systems and high-throughput data pipelines. Own reliability, performance, testing, documentation, and production readiness; participate in on-call support. Mentor engineers, lead design reviews, investigate incidents, and collaborate with stakeholders to develop effective tooling across the Temporal ecosystem.

Leads and coaches a software engineering team, supports career development, participates in hiring, removes delivery roadblocks, and shapes technical direction. The manager ensures reliable, high-performing systems while driving daily adoption of agentic AI tools and collaborating with Product and Business Technology stakeholders. The role requires a strong full-stack engineering background, architectural expertise, experience delivering quality software, and demonstrated success leading AI adoption.

Designs, develops, and maintains infrastructure for ML pipelines and CI/CD. Analyzes infrastructure performance, collaborates with data and software teams, manages feature stores and model registries, writes maintainable code, and documents technical processes. The role requires experience with cloud, big-data, programming, workflow orchestration, version control, and continuous integration technologies.

Build and operate large-scale distributed web crawlers that discover, fetch, extract, deduplicate, and recrawl billions of pages. Develop targeted pipelines for audio, video, and multilingual data, transforming web content into training-ready datasets. Create infrastructure and tooling for researchers to request, monitor, evaluate, and explore crawled data, while ensuring reliability, efficiency, compliance, politeness, and rate-limit handling.

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.