Top Remote Principal Software Engineer Jobs

Design and build Azure Kubernetes Service features and AI-native infrastructure, improve service reliability and developer velocity, automate incident prevention/remediation, integrate AI tools, and operate distributed, containerized systems at cloud scale.

Lead architecture and roadmap for Azure PostgreSQL systems; design and review scalable, maintainable database engine features (query processing, storage, transaction logging, recovery, versioning, IO, scale-out). Influence coding standards and run code reviews, write proof-of-concept or production code, contribute to open-source PostgreSQL/Linux, and participate in rotational on-call operations.

Build and operate Legion’s secure, scalable AWS and Kubernetes platform. Responsibilities include infrastructure automation, CI/CD, monitoring, alerting, incident response, operational runbooks, production support, and on-call participation. The role also develops production AI agents for SRE automation and owns a secure platform for engineering teams to build and operate agents with sandboxing, scoped credentials, integrations, cost controls, observability, and reliability guardrails.

Lead the architecture, development, testing, and deployment of hyperscale distributed storage systems optimized for AI and machine learning workloads. Drive innovations in scalability, performance, security, durability, and efficiency while collaborating with AI researchers and cloud infrastructure teams. Mentor engineers, guide technical strategy, and help shape Azure Blob Storage into an AI-native platform supporting zettabyte-scale storage.

Principal Software Engineer role at Atlassian with flexible remote, office, or hybrid work options. The provided description primarily details compensation, benefits, company culture, equal employment practices, and employment verification requirements; specific responsibilities and technical qualifications are not included.

Provides technical leadership on complex software projects from design through launch, addressing architecture, reliability, security, testing, and observability at scale. Leads company-wide engineering initiatives, establishes technical standards, mentors engineers, and promotes engineering excellence. Requires extensive full-stack development experience, strong communication, systems engineering expertise, customer-focused decision-making, and familiarity with A/B testing.

Leads complex software engineering initiatives from technical design through launch, provides architectural and technical leadership, drives engineering standards, mentors engineers, and collaborates across teams on company-wide projects. Requires deep experience building and operating scalable systems with strong testing, reliability, security, and observability practices, plus full-stack development expertise and familiarity with A/B testing.

Lead the design and implementation of a distributed compute control plane for managing virtual machines across Akamai’s cloud fleet. Own database partitioning and sharding, placement reconciliation, asynchronous operations, consistency guarantees, idempotency, fencing, and saga-style workflows. The role requires deep distributed systems, database, containerization, Kubernetes, and controller-pattern expertise, along with strong Python or Go development skills.

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.

Develops and maintains high-quality systems software and microservices for Azure Messaging services, including data storage and replication. Drives product and engineering-process innovation, applies AI to software development, ensures software quality and stability, and uses rigorous development practices including requirements, testing, and efficient coding techniques.

Leads architecture and development of Azure Storage table, metadata, and indexing systems at massive cloud scale. Designs distributed-system primitives for partitioning, indexing, transactions, consistency, replication, caching, and high-performance data access. Drives architectural decisions, prototypes innovations through production, and improves performance, scalability, reliability, and cost efficiency. Requires deep expertise in distributed storage, databases, or large-scale systems.

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.

Leads the design and development of scalable SaaS applications, including AI-powered features such as semantic search, vector databases, RAG, and LLM orchestration. Provides technical leadership, mentorship, architectural guidance, code reviews, and engineering standards enforcement. Collaborates cross-functionally to translate requirements into robust solutions, champions AI-assisted development tools, builds developer experience tooling, and drives innovation, quality, security, and continuous improvement across the engineering organization.

Define architectural direction for Azure Specialized platform services and lead the design of highly available distributed cloud systems. Drive reliability, scalability, observability, security, diagnostics, and operational improvements across engineering organizations. Establish service health frameworks, SLOs, metrics, and governance for mission-critical services. Mentor engineers, influence technical strategy, resolve complex cross-system challenges, and advance AI-assisted troubleshooting and platform modernization.

Leads the roadmap, architecture, security, and organizational adoption of CI/CD and release infrastructure. Designs scalable release gates, hardens supply chains, directs engineers through complex projects, manages severe incidents, and drives cross-functional technical alignment. The role remains hands-on through code reviews, prototyping, debugging, documentation, mentorship, and design reviews while primarily achieving impact through team leadership.

Design, build, and operate distributed storage and file-system platforms for cloud-scale AI training and inference. Architect storage and caching for Kubernetes and GPU workloads, improve performance, reliability, observability, and resiliency, diagnose cross-layer production issues, and lead architecture reviews. Partner across infrastructure, networking, operating systems, and AI platform teams while mentoring engineers and shaping long-term storage strategy.

Lead the architecture, technical strategy, and roadmap for Microsoft's Windows ML compiler stack. Design high-performance compiler infrastructure, execution engines, optimization frameworks, and developer tools supporting CPU, GPU, and NPU workloads. Drive NPU enablement, graph optimization, scheduling, memory management, code generation, and hardware abstraction. Partner with silicon vendors and internal teams, influence AI hardware and platform strategy, lead cross-team initiatives, and mentor engineers developing on-device and generative AI capabilities.

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.

Leads architecture and hands-on development for AI frameworks, performance systems, benchmarking, and developer tools. Investigates issues across models, compilers, runtimes, services, and accelerator hardware; improves model onboarding, runtime performance, reliability, hardware utilization, and Azure efficiency. Establishes scalable measurement and observability capabilities, influences cross-team technical strategy, delivers production solutions, and mentors engineers while advancing engineering quality and maintainability.

Owns architecture and hands-on development across a production AI platform for pharmacy and healthcare. Builds scalable systems, safe voice and SMS agents, EHR integrations with Epic, prior authorization automation, and reliable AI evaluation and guardrails. Leads complex cross-team projects, mentors engineers, improves engineering practices, and advances agentic development. Requires recent Staff+ level system-building experience, production LLM expertise, strong architectural judgment, and experience operating in high-compliance or high-consequence environments.

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.

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.

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.

Work on end-to-end AI performance for LLMs: benchmark and optimize inference on GPUs and Microsoft silicon, build tooling for performance insights and model porting, implement and test components in AI/DNN frameworks, and collaborate with internal and external partners to reduce hardware footprint and accelerate deployments.

Lead development of a massively distributed edge compute platform. Design fault-tolerant systems, external APIs, high-throughput traffic routing, and Kubernetes-based resource management. Establish architecture standards, reliability metrics, security practices, and technical governance. Collaborate with AI/ML, hardware, networking, and security teams; communicate risks to executives; manage customer requirements; review code; and mentor engineers on distributed systems best practices.