Top Remote Software Engineer Jobs in Boston, MA

Deploy and integrate Shield AIs Hivemind autonomy software with customers worldwide. Provide on-site technical support, training, debugging, and documentation. Collaborate with sales and product engineering to support pre- and post-sales activities and improve autonomy products.

Lead architecture and hands-on development of a scalable fraud and payment risk platform. Build backend services, APIs, feature pipelines, configurable rules, experimentation infrastructure, and machine-learning lifecycle tooling. Own reliability, observability, monitoring, performance, and safe production deployments. Collaborate with product, risk policy, data science, and engineering teams while mentoring engineers and driving complex initiatives from design through production.

Build full-stack geospatial applications and platform components for defense and intelligence users. Develop interactive mapping tools with TypeScript, React, Tailwind, Node.js, and PostgreSQL; design reusable map components; ingest, analyze, and visualize high-volume geospatial data; integrate agentic AI analyses; and collaborate with customers, mission owners, designers, and engineers to create intuitive operational workflows.

Lead full-stack engineering for Rula’s patient portal, designing scalable, secure, and reliable systems across scheduling, billing, communications, and treatment planning. Own technical direction, architecture, complex initiatives, and long-term improvements while mentoring engineers and collaborating cross-functionally. Build and operate solutions using React, TypeScript, Node.js, microservices or event-based architectures, Kafka, and AWS. Participate in on-call support and troubleshoot production issues.

Design, develop, test, deploy, and monitor scalable backend systems for a payroll SaaS product. Build APIs and microservices, collaborate with product and engineering teams, participate in code reviews, and own the full development lifecycle in a continuous delivery environment. The role emphasizes Kotlin, Scala, or Java, cloud platforms, automated testing, relational databases, scalable architecture, and responsible use of AI coding tools.

Leads software engineering across broker productivity products and core platform squads. Owns engineering delivery, infrastructure and security roadmaps, cross-squad practices, migrations, integrations, testing, and compliance remediation. Partners with product and company leadership, hires and develops senior engineers and tech leads, and builds scalable engineering management structures. The role remains hands-on through design reviews, specifications, code reviews, and technical spikes.

Build and scale backend product features and cloud services supporting distributed systems, AI agent workflows, high-performance APIs, and large-scale data processing. Responsibilities include designing reliable, fault-tolerant, highly available services; developing tool-calling APIs, workflow orchestration, observability, and production guardrails; meeting service-level commitments; and collaborating through code reviews and knowledge sharing.

Architects, builds, and operates resilient backend services, cloud infrastructure, automation tools, and self-service interfaces supporting MDR and incident response operations. Partners with security practitioners and engineering teams to translate operational needs into scalable solutions, establish CI/CD and observability practices, improve reliability, and integrate AI-driven workflows. The role also provides technical mentorship, leads architecture and design decisions, and drives complex initiatives through iterative delivery.

Own backend engineering goals for Consumer Engineering, lead delivery of scalable systems, collaborate with product, design, and analytics, improve reliability and code quality, resolve technical and business issues, support on-call operations, and mentor engineers.

Design and evolve high-scale backend capabilities for GitLab’s container registry. Drive architecture, performance, reliability, security, APIs, testing, and operational readiness. Mentor engineers, influence technical direction, participate in incident response, and collaborate asynchronously across product, infrastructure, data, frontend, and security teams. Integrate and evaluate agentic AI systems in production engineering workflows while promoting responsible and effective use.