Top Remote Principal Software Engineer Jobs in Austin, TX

Build and evolve server and agent tool surfaces for LLM clients, ship frontend features and tRPC/React routes, design public API layer with auth and rate limiting, integrate new data sources, and own performance, reliability, security, and observability end-to-end.

Lead development and optimization of high-performance LLM inference pipelines across data center, edge, and embedded platforms. Improve latency and throughput via custom CUDA kernels, quantization, KV-cache and batching strategies, and deploy efficient, production-ready runtimes without external vendor dependency.

Design, develop, and maintain scalable AI-forward APIs, MCPs, and services for Microsoft 365. Lead features from concept through launch, write reusable code, document designs, estimate work, and support production services through on-call responsibilities. Improve reliability, performance, and scalability while mentoring engineers and establishing technical best practices across teams.

Design and build distributed storage systems optimized for AI and machine learning workloads at hyperscale. Lead architecture, development, testing, deployment, scalability, performance, security, and efficiency initiatives for zettabyte-scale Azure storage. Collaborate with AI researchers and cloud infrastructure teams, mentor engineers, evaluate emerging technologies, and solve complex problems involving availability, durability, replication, high-performance I/O, metadata, indexing, caching, and data placement.

Lead Elasticsearch performance engineering from architecture through production. Develop performance models, optimize distributed systems, profile bottlenecks, build benchmarks, detect regressions, and improve scalability across stateful and serverless architectures. Design AI-assisted optimization and benchmarking tools, collaborate across teams, define performance strategies, and mentor engineers. The role requires deep Java, JVM, concurrency, distributed systems, and search or data-store performance expertise.

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.

Design and develop software to onboard hardware accelerators and optimize storage datapaths for Azure Storage. Drive design, debugging, performance tuning, operations, and cross-team collaboration across research, compute, and storage to improve throughput, scale, reliability, and observability.

Design and deliver large-scale, cloud-native and AI-enabled Kubernetes/AKS solutions. Implement, optimize, and maintain Kubernetes components and container orchestration across Azure, on-prem, and edge. Integrate AI capabilities, participate in on-call rotations, mentor engineers, and collaborate cross-functionally to improve reliability, observability, performance, and operational consistency at scale.

Leads the technical strategy, architecture, implementation, and delivery of a scalable ecommerce platform for vehicle discovery, configuration, checkout, payments, order management, fulfillment, and ownership experiences. Builds and tests distributed systems, drives code quality and technical decisions, partners with product and UX teams, simplifies complex problems, and mentors engineers while balancing customer impact, business needs, and long-term technology excellence.

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.

The role involves leading initiatives for vector search in Elasticsearch, enhancing features, resolving bugs, and contributing to community engagements in a distributed team setting. A strong background in vector similarity and Java is crucial.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

Lead technical ownership and hands-on engineering for the integration backbone of a financial SaaS platform. Modernize legacy integration processes into .NET services, design reliable REST and file-based connectors, optimize Oracle SQL/PL/SQL, improve observability, and drive cloud-native Azure patterns. Mentor engineers, enforce standards, and champion AI-first development to increase delivery velocity and operational quality across multiple production ecosystems.

Lead design and implementation of scalable SaaS applications with advanced AI features (semantic search, vector DBs, RAG, LLM orchestration). Translate business needs into technical designs, mentor engineers, enforce code quality and CI/CD, champion AI-assisted tooling, and drive architectural integrity and developer experience across the organization.

Lead platform strategy, architecture, and hands-on development. Design, build, deploy, and operate high-performance, fault-tolerant integrations and platform enhancements. Drive security/compliance, mentor engineers, recruit senior talent, align technology with business goals, and communicate technical vision to stakeholders.

Design and implement scalable full-stack solutions for institutional platforms. Lead API and microservices design, cloud (AWS) deployments, CI/CD and DevSecOps, collaborate with product and QA, troubleshoot production, and mentor distributed teams.

Design, architect, and build enterprise Java microservices and APIs; lead technical delivery, mentor engineers, implement cloud-native and CI/CD practices, design database schemas and PL/SQL, and develop blockchain/digital-asset solutions including smart contract work and lifecycle integration in financial services.

Lead technical vision and architecture for Dockers Developer Tools: build a self-service internal platform, CI/CD and build systems, integrate AI/LLM agents, set SDLC tenets, establish standards for observability, security, reliability, and productize internal tooling into customer offerings.

Lead technical direction for a major product domain, reduce architectural debt, mentor engineers, standardize AI-agent workflows, and design scalable backend solutions integrating LLMs and cloud services. Drive cross-team RFCs, cookbook standards, and adopt agentic AI tooling while balancing security, quality, and delivery.

Lead end-to-end design, development, and quality of enterprise cloud solutions. Estimate costs, define quality criteria, implement complex systems, manage engineering processes, risks, and dependencies, and mentor teams. Serve as technical lead across large, cross-functional projects to deliver measurable, user-centric healthcare technology solutions.

Lead frontend technical direction for the Trellis design system: design and build a production component library, define accessibility and theming models, create tooling and migration pipelines (codemods, refactoring automation), leverage AI coding agents, mentor senior engineers, and partner with PM/UX to drive frontend architecture and adoption across product teams.

Lead architecture and evolution of Cardlytics' AWS-based data compute platform and lakehouse. Define standards for batch, streaming, ML, and AI workloads; build semantic layer, feature store, and governance. Partner with analysts and engineers, drive CI/CD (Terraform, GitHub Actions), monitoring, security, cost governance, and incident response while mentoring teams and shaping platform strategy.

Design, build, and maintain a secure, high-performance browser extension (Manifest V3) for Chrome/Edge and major browsers. Implement secure interactions with web content and backend services, optimize reliability, collaborate with endpoint and backend teams, and stay current on browser APIs and security standards.

Drive architecture and technical vision for Elasticsearch core storage and query engine. Lead performance and storage-efficiency improvements, design indexing/serialization/data layouts, mentor engineers, coordinate cross-organizational initiatives, triage community issues, and write idiomatic modern Java for logs and metrics workloads.

Lead architecture and build Aura's AI Intelligence Platform, unifying data and enabling AI agents to reason over sensitive information. Own end-to-end initiatives, prioritize security and privacy, design scalable distributed systems on AWS using Python and TypeScript, and set engineering best practices while mentoring engineers without direct reports.