Top Remote Principal Software Engineer Jobs in Chicago, IL

Provides technical leadership for real-time RF sensor software development, integration, testing, and validation. Designs high-performance C/C++ systems, integrates signal-processing algorithms, debugs distributed and multithreaded applications, and transitions MATLAB/Python prototypes into production software. The role includes technical mentoring, customer and government stakeholder engagement, proposal development, documentation, system demonstrations, visualization tools, and approximately 10% travel for integration and field-testing activities.

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.

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.

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.

Lead the architecture and technical direction of Forward Financing’s core fintech platform. Design scalable distributed backend systems, guide cross-team initiatives, establish engineering best practices, resolve incidents, and mentor engineers. The role owns the technical roadmap and architectural vision while partnering across teams to improve reliability, observability, code quality, and delivery. Ruby on Rails expertise is required, along with strong communication, influence, agile development experience, and a broad backend or full-stack perspective.

Leads architecture and development of SailPoint’s large-scale, multi-tenant identity security SaaS platform. Translates business strategy into technical roadmaps, designs reliable microservices and infrastructure, drives modernization from monoliths to distributed systems, mentors engineers, reviews designs, delivers code, and communicates technology strategy to executives and stakeholders. The role also requires adoption and oversight of AI-assisted engineering tools and technologies.

Designs and develops internet-scale data processing, infrastructure management, and observability platforms across cloud and on-premises environments. Establishes engineering standards, resolves complex distributed architecture challenges, and provides technical leadership across the organization. The role requires experience with large-scale orchestration systems, internet protocols such as DNS, WHOIS, and RDAP, architectural trade-offs, and internet security technologies.

Founding engineer responsible for architecting and building core product components, writing scalable Python code, designing and maintaining AI/ML infrastructure, implementing testing and CI/CD best practices, shipping backend production systems, collaborating on product roadmap, and mentoring future engineers.

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.

Own the architecture and technical direction of NodeZero’s database platform. Design scalable PostgreSQL and graph-based data systems, multi-tenant schemas, partitioning, replication, indexing, and zero-downtime migrations. Establish database standards, governance, performance practices, and migration tooling while writing production code. Mentor engineers, lead architecture reviews, and collaborate across data, inventory, API, and security teams to ensure reliable, isolated, and scalable data infrastructure.

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.

Work with customers and cross-functional teams to design, build, and deliver cloud-based solutions. Lead design, identify dependencies, mentor engineers, act as DRI and on-call, and improve availability, reliability, observability, and performance. Contribute to open-source assets and collaborate with Microsoft product teams to produce extensible, maintainable code and scalable solution patterns.

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.

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.

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 the architecture and hands-on development of agentic observability capabilities for Kubernetes and Linux. Build production-quality software, interpret systems telemetry using eBPF, mentor engineers, coordinate cross-team delivery, support open-source initiatives, and participate in on-call operations. The role focuses on safe, observable, and evaluable AI-agent workflows, distributed systems reliability, and technical leadership across engineering teams.

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.

Lead design, development, and operation of highly available AKS Resource Provider and control-plane services. Drive cluster lifecycle, upgrades, networking, security, scalability, observability, resiliency, and incident prevention for large-scale distributed cloud systems. Collaborate across Azure engineering teams, lead architectural decisions, improve tooling and automation, troubleshoot production issues, and mentor engineers while supporting reliable Kubernetes workloads across cloud and edge environments.

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 responsible for operating and improving business-critical data pipelines and infrastructure. Duties include developing monitoring, alerting, logging, CI/CD workflows, scalable data integrations, automated testing, deployment automation, and production support. The role troubleshoots workflow failures, data-quality issues, performance bottlenecks, and infrastructure incidents while collaborating with data engineers, platform engineers, and architects. Preferred experience includes Databricks, Spark, AWS, Terraform, Unity Catalog, Delta Lake, observability, identity management, and enterprise data platform governance.