Top Remote Principal Software Engineer Jobs in Austin, TX

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.

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.

Own the architecture and technical direction of NodeZero’s database platform. Design scalable PostgreSQL systems, multi-tenant data models, graph-based asset models, partitioning, replication, and zero-downtime schema migrations. Establish database standards, governance, and performance practices while writing production code, authoring design documents, mentoring engineers, and influencing teams across the data pipeline.

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.

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.

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.

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.

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.

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.

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.

Leads and contributes hands-on to development of an AI engineering platform for semiconductor testing. Designs agent tooling, RAG systems, cloud and air-gapped inference infrastructure, Kubernetes platforms, reusable AI patterns, and agent-facing UIs. Sets technical direction, selects hardware and inference stacks, manages production systems, resolves cross-team architecture decisions, and guides a small engineering team. Requires strong distributed systems, software development, leadership, communication, and LLM/agent tooling expertise.

Leads end-to-end software development for AI-infused enterprise applications, including architecture, database design, coding, testing, deployment, and service reliability. Builds Copilot and agentic solutions using Azure and modern full-stack technologies. Provides technical leadership, mentors engineers, establishes quality and security practices, supports enterprise integrations, and collaborates with product teams, program managers, UX designers, and data scientists to deliver scalable commercial software.

Lead architecture and development for AKS Flex, scaling etcd and Kubernetes control planes for distributed node fleets. Design remote-node provisioning, lifecycle automation, Kubernetes-native APIs, secure bootstrap, upgrades, and reliability systems across Azure, on-premises, edge, and other clouds. Drive performance testing, production operations, open-source collaboration, technical strategy, cross-team alignment, and mentorship while solving distributed-systems, storage, security, and scalability challenges.

Leads development of distributed AI infrastructure for large-scale reinforcement learning and LLM post-training. Designs scalable, resilient systems; optimizes model, hardware, and inference performance; improves developer tooling and engineering practices; mentors engineers; and supports production services through reliability engineering, incident response, telemetry, and on-call operations.

Own the core software architecture for a laser-driven fusion power plant. Design and implement C++ and Python software integrating controls, hardware interfaces, calibration systems, data infrastructure, storage, and operator HMIs. Establish standards for testing, observability, reliability, security, fault tolerance, documentation, and releases. Lead technical decisions, mentor engineers, resolve architectural trade-offs, and collaborate across software, hardware, science, and operations teams.

Lead technical direction for Elastic’s core billing platform across cloud providers. Design and operate scalable billing systems, data pipelines, APIs, and PostgreSQL architecture. Improve reliability, observability, incident response, deployment, and CI/CD practices. Partner with SRE, Cloud Infrastructure, Product, Design, and Finance teams, guide architecture and roadmap decisions, review technical work, mentor engineers, and participate in on-call rotations.