Top Remote Principal Software Engineer Jobs in Boston, MA

Owns company-critical, long-term technical problems across multiple teams and organizations. Defines technical strategy, architectures, roadmaps, and engineering standards for large-scale customer-facing systems. Remains hands-on in software development while driving AI adoption in products and engineering workflows. Partners with senior product, engineering, and executive leaders to resolve complex problems, improve reliability and performance, and shape Dropbox’s technical direction.

Lead the mobile engineering team in evolving iOS and Android applications toward an AI-native, thin-client architecture. Define participant API and platform direction, contribute Python to backend services, establish AI-assisted development processes, improve DevOps and continuous delivery, mentor engineers, and partner closely with Product and Design. The role requires principal-level technical leadership, product focus, system architecture expertise, and hands-on use of AI coding agents.

Leads architecture and hands-on development of WEX’s semantic data platform and Data-as-a-Service capabilities. Builds reusable semantic business objects, metadata and ontology frameworks, knowledge graphs, APIs, governance, lineage, quality, and data contracts. Solves distributed-systems and scalability challenges while enabling AI and agentic applications to use trusted enterprise data. Partners across engineering, product, analytics, risk, finance, and business teams; influences technical standards, drives adoption, mentors engineers, and remains involved in implementation.

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.

Architects scalable distributed systems and low-level cloud platform services, establishes engineering standards and SLOs, designs CI/CD and deployment safety pipelines, leads complex incident escalations and postmortems, and mentors engineering teams. The role requires full-stack, API, and microservices development in Linux or Unix environments, strong SRE expertise, architectural leadership, and US citizenship with eligibility for security clearance.

Provides technical leadership for AI framework and model-serving initiatives at cloud scale. Owns architecture, roadmaps, performance optimization, benchmarking, observability, and multi-release execution across models, compilers, runtimes, services, GPUs, and silicon. Leads cross-team alignment, makes architectural decisions, mentors engineers, performs hands-on implementation and debugging, and drives measurable improvements in model onboarding, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.

Design and evolve distributed search and analytics systems for the Splunk platform. Lead complex engineering efforts from design through delivery, improve performance and reliability, mentor engineers, collaborate cross-functionally, and work with customers to resolve production issues.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Leads the design and implementation of highly scalable Azure messaging and PubSub services. Defines architecture, testing strategies, coding standards, and reusable engineering frameworks; mentors engineers and conducts design and code reviews. Drives incident response, root-cause analysis, service reliability, SLA compliance, and operational improvements. Partners with stakeholders and customers to shape requirements and product direction, while advancing responsible AI practices throughout the software development lifecycle.

Design, implement, and ensure quality of systems stack, tools, and SDK integration for AI frameworks. Collaborate with hardware and ML teams, apply engineering principles, write low-level/high-performance code, define architecture, estimate scope, and drive coding standards.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Leads architecture and production delivery of a near-real-time observability platform for large-scale AI supercomputers. Responsibilities include telemetry ingestion, processing, storage, querying, topology and health modeling, 1P/3P data convergence, AI-assisted anomaly detection, technician dashboards, repair validation, security, reliability, cross-team technical leadership, and mentoring.

Design and lead development of high-performance networking infrastructure for large-scale AI training and inference in Azure. Architect low-latency, low-jitter communication frameworks, optimize distributed systems, benchmark scalability, resolve complex networking issues, and improve reliability, observability, and performance. Mentor engineers, create technical designs, manage dependencies, and participate in on-call operations for critical services.

Leads engineering within a product domain, driving large-scale strategic initiatives across multiple teams. Establishes technical standards, architecture, and scalable best practices; aligns engineering, product, data science, and business stakeholders; guides roadmaps and resource allocation; communicates with executives; and coaches engineering leaders and senior individual contributors.

Build and own Arcadia’s internal developer platform across a large-scale data lakehouse and Kubernetes applications. Develop self-service APIs, templates, golden paths, CI/CD capabilities, observability, security controls, and reliability practices. Lead platform migrations, improve developer experience, manage stakeholder needs and costs, set technical direction, and coach senior engineers. The role requires hands-on software development alongside expertise in cloud infrastructure, Kubernetes, networking, infrastructure as code, SLOs, incident response, and platform product management.

Designs and develops secure, performant Copilot products and platform services across Windows, Mac, and mobile. Builds distributed AI and agent-driven systems capable of reasoning, planning, and executing tasks. Collaborates with infrastructure, platform, application engineering, and research teams to ship high-quality software. Champions AI-assisted development, coding-agent adoption, prompt design, tooling best practices, and human-in-the-loop systems.

Develop and optimize GPU kernels, compilers, runtimes, and distributed inference systems for large language model serving. Improve latency, throughput, reliability, and hardware efficiency through profiling and low-level performance optimization. Integrate scalable improvements into production systems, collaborate across model, infrastructure, compiler, and hardware teams, and mentor engineers. Principal-level contributors additionally lead cross-stack initiatives and create reusable performance capabilities across models and hardware generations.

Lead architecture and hands-on development of Microsoft's AI Safety Platform, building observability, detection, investigation, threat-hunting, and distributed data-processing capabilities. Design attack detection infrastructure, correlate high-volume telemetry, apply AI security research, conduct security and privacy reviews, and partner across engineering, science, and incident response teams. Mentor engineers and provide technical leadership for complex AI security systems.

Lead architecture and hands-on development for Microsoft's virtualization platform, focusing on hypervisor and VMM capabilities. Design, implement, and optimize systems software across Windows, Linux, macOS, Azure, and containers. Improve performance, security, reliability, testing, and operational readiness; diagnose low-level hardware/software issues; enable virtualization on new silicon; mentor engineers; and influence platform strategy across teams and hardware partners.

Design, implement, and operate production-quality AI framework components, benchmark and optimize large model training and inference across GPUs and Microsoft hardware, build automation and observability, drive cross-team projects from definition to deployment, and provide technical leadership and mentorship for improvements in performance, reliability, and model onboarding velocity.

Build and improve Azure Kubernetes Service capabilities for Linux and Windows containers. Develop distributed cloud infrastructure, automation, observability tooling, and reliability improvements at global scale. Support AI-native infrastructure, including GPU orchestration, model deployment, inference, and platform operations. Accelerate engineering workflows, prevent production incidents, integrate AI tools, and contribute to Kubernetes and cloud-native platform innovation.

Lead technical vision and architecture for AI frameworks, performance, benchmarking, and tooling. Drive cross-team alignment, mentor engineers, ship high-performance distributed software, and improve model onboarding, runtime performance, reliability, and Azure hardware efficiency.

Lead the architecture and development of a production Agentic SOC that uses LLM-based agents to investigate security signals, gather evidence, make defensible decisions, and support SOC analysts. Own agent behavior, tool use, evaluation, guardrails, tenant isolation, auditability, reliability, and autonomous decision-making. Collaborate with analysts, detection engineers, product, and engineering teams while providing technical leadership and mentoring. Build scalable backend systems using distributed workflows, queues, cloud infrastructure, and data stores.

Design, develop, deploy, and operate cloud-scale Azure regional networking infrastructure spanning router hardware, operating systems, optical transceivers, and distributed orchestration systems. Lead architecture and cross-team technical initiatives, write maintainable code, improve reliability, observability, performance, and automation, apply AI-driven engineering practices, and mentor engineers while collaborating with hardware, supply chain, datacenter operations, research, vendors, and senior leaders.

Own the architecture, implementation, and operational excellence of major Azure Boost DPU software components. Develop low-level systems software spanning operating systems, virtualization, networking, storage, device management, and hardware interfaces. Lead complex cross-functional initiatives, optimize hyperscale performance and reliability, resolve system-level issues, establish engineering practices, influence platform architecture, and mentor engineers across Azure infrastructure teams.