Top Remote Senior Backend Engineer Jobs in Boston, MA

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.

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.

Own quarterly engineering goals, lead backend engineers through ambiguous problems, collaborate with product and analytics partners, improve system reliability and availability, monitor operational metrics, establish quality standards, and mentor team members. The role requires designing and launching highly available distributed backend systems at scale using Python or Kotlin, AWS, MySQL, and Kubernetes, while driving technical planning and safe changes across large codebases.

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.

Architect and operate Affirm’s large-scale Amazon EKS compute platform, including cluster lifecycle, node management, autoscaling, shared components, infrastructure automation, workload safety policies, observability, cost and capacity optimization, and self-service workflows. The role drives technical strategy, mentors engineers, partners cross-functionally, and participates in on-call incident response.

Build and operate Affirm’s AI platform, including LLM and MCP gateways, agent runtimes, evaluation services, and governance controls. Design highly available backend systems, manage identity, quotas, routing, caching, reliability, observability, and security for AI workloads. Own projects from design through launch and on-call, establish engineering standards, collaborate across teams, mentor engineers, and help scale AI systems into production.

Build and enforce workload safety standards across Affirm’s Amazon EKS fleet. Responsibilities include Kubernetes resource management, workload isolation, disruption handling, cluster capacity analysis, policy automation, production debugging, incident response, fleet-wide rollouts, technical leadership, mentoring, and measuring infrastructure impacts on availability, latency, risk, and cost.

Build and ship backend features end-to-end using Ruby on Rails and SQL. Lead complex technical projects, solve architecture challenges, establish standards, conduct meaningful code reviews, resolve high-risk bugs, document systems, collaborate across engineering teams, and mentor junior engineers.

Design and implement Mojo compiler features, optimization passes, and code generation for CPUs, GPUs, and AI accelerators using MLIR and LLVM. Collaborate with kernel authors, hardware engineers, researchers, and open-source contributors to improve compiler performance, language design, developer experience, and the broader Mojo technology stack.

Design, build, and maintain backend systems for payments, subscriptions, billing, and revenue workflows. Develop APIs, integrations, event-driven processing, database models, reconciliation tools, access controls, testing, monitoring, and reliability safeguards. Own complex initiatives from architecture through production, investigate incidents, collaborate with finance and product teams, and provide technical guidance while using AI-assisted development tools responsibly.

Lead technical vision and strategy for Affirm’s Cards backend engineering organization. Architect scalable and reliable platforms, guide cross-team initiatives, champion AI adoption and engineering excellence, influence technical roadmaps, and mentor engineers through Staff level. The role requires strong architectural expertise, organizational leadership, project management, communication, and cross-functional collaboration.

Own and deliver backend lakehouse infrastructure goals, lead engineers through complex problems, and build highly available distributed data systems. Collaborate with product, design, analytics, and engineering stakeholders; define scalable technical solutions; improve code quality and engineering standards; monitor operational health; support on-call responsibilities; and mentor team members.

Own backend features from inception through production, develop and improve Kotlin services, write maintainable and well-tested code, and design scalable, reliable distributed systems within a small cross-functional team.

Designs and scales high-performance backend web services and ETL pipelines supporting tens of thousands of transactions per second. Responsibilities include architecting fault-tolerant distributed systems, improving performance, developing monitoring and deployment strategies, collaborating across product and engineering teams, and supporting recruiting and onboarding. The role requires expertise in data-intensive systems, microservices, cloud architectures, and commercial SaaS products.

Lead development of scalable backend services and data platforms using Scala and Rust. Design distributed systems, APIs, data pipelines, and security-data workflows; guide Scala-to-Rust migration; support Python-based malware analysis, threat detection, and machine learning systems. Own production reliability, architecture, code quality, reviews, deployment, observability, and incident response in a cloud-native environment.

Develop and improve core software services supporting customer intake, application screening, and information dissemination. Design distributed, microservice-based systems; identify bottlenecks; improve reliability, scalability, and business logic; and contribute to modernization and architectural decisions. Work independently across the stack, communicate technical trade-offs, mentor junior developers, and use AI and automation tools to improve engineering outcomes.

Design and scale asynchronous Python backend systems, including REST/WebSocket APIs, multi-agent LLM workflows, provider-agnostic integrations, and RAG pipelines. Own relational data models, observability, performance, CI/CD, and production deployment. Establish AI governance covering code review, provenance, licensing, security, compliance, and customer data handling. Drive ideas from concept through production while owning architecture and outcomes.

Leads architecture, development, and operation of Python-based AWS backend and IoT cloud services. Designs Lambda microservices, REST APIs, event-driven workflows, telemetry pipelines, data models, and AWS IoT Core integrations. Provides hands-on technical leadership through coding, design and code reviews, mentoring, planning, and standards development. Ensures security, scalability, observability, CI/CD, production readiness, incident response, and cross-functional alignment across firmware, mobile, QA, DevOps, Product, and Security teams.

Develop scalable Django back-end applications and RESTful APIs; design databases, schemas, ER diagrams, data flows, authentication, and authorization systems. Configure cloud infrastructure and production deployments, optimize PostgreSQL performance, write automated tests, and manage Linux servers with Bash, SSH, and shell scripting. Collaborate with cross-functional teams, document systems, and contribute to scalable architecture. This is a remote, unpaid internship requiring at least 30 hours weekly.

Build and scale backend infrastructure for AI-driven freight finance workflows, including document processing, APIs, data pipelines, audit engines, integrations, observability, and performance monitoring. Collaborate with AI/ML teams to productionize model outputs, integrate freight and financial systems, improve engineering practices, and make frontend updates as needed in a remote-first startup environment.

Build and operate backend services and APIs for secure, multi-tenant administration workflows, including user access, account hierarchies, settings, roles, access controls, and audit logs. Own features from design through production support, applying strong data modeling, authorization, testing, observability, and reliability practices. Collaborate with Product and engineering teams, investigate production issues, document systems, and mentor teammates.

Build and operate highly scalable Go backend services and data infrastructure for the AT Protocol ecosystem. Scale systems to support hundreds of millions of users, hundreds of millions of events, petabytes of NVMe storage, thousands of CPU cores, and tens of terabytes of RAM. Responsibilities include developing mission-critical services, managing production operations, and working with databases, distributed systems, operating systems, networking, and storage technologies.

Designs, develops, and supports scalable Java microservices using Spring Boot and Google Cloud. Responsibilities include SQL and data pipeline development, CI/CD automation with Jenkins, infrastructure as code using Terraform, unit testing, code reviews, production incident resolution, root-cause analysis, agile execution, and mentoring engineering teams.

Build and operate backend services and asynchronous workflows that provision customer accounts, assets, and product entitlements. Own projects from design through production support, ensuring reliable retries, idempotency, observability, testing, and recovery from failures. Collaborate with licensing, Product, administration, partner, and customer-facing teams to improve onboarding and activation paths. Investigate operational issues, address root causes, document systems, and contribute to code reviews and technical problem solving.

Design and own backend infrastructure for a privacy-first AI memory platform. Responsibilities include multi-tier memory storage, secure multi-tenant isolation, real-time APIs, caching, LLM integrations, retrieval systems, synchronization, monitoring, deployment pipelines, and production reliability. The role requires close collaboration with ML engineering and product teams while owning architecture, infrastructure, testing, security, and operational troubleshooting.