Top Principal Software Engineer Jobs in Austin, TX

Lead legacy application assessments and modernization strategy for U.S. Air Force systems. Own architectural decisions, technical direction, and test strategy while collaborating with government engineers, vendors, product managers, researchers, and designers. Promote secure, compliant, agile engineering practices; coach government teams; evaluate technical environments; communicate recommendations; and demonstrate modern AI-assisted development practices. The role is fully remote, requires U.S. citizenship and CAC eligibility, and involves occasional quarterly travel to Air Force bases.

Lead end-to-end design and delivery of AI-infused, enterprise full-stack applications on Azure. Architect resilient solutions, build Copilot/agentic features, enforce engineering best practices, mentor engineers, collaborate with PM/UX teams, ensure quality/reliability, and support production services and integrations.

Design and implement PostgreSQL internals, indexing, query engine extensions, and storage-layer features to support large-scale document workloads on Azure. Profile distributed systems, tune performance, collaborate with open-source communities, conduct design/code reviews, and drive cross-team alignment for mission-critical database features.

Leads the technical vision, architecture, and execution of AI performance, framework, benchmarking, and developer-productivity initiatives. Drives cross-team architecture, resolves complex systems trade-offs, mentors technical leaders, and contributes hands-on through prototyping, implementation, reviews, debugging, observability, and automation. Delivers measurable improvements in model onboarding speed, runtime performance, reliability, hardware utilization, and Azure capacity efficiency across models, frameworks, compilers, runtimes, systems, services, and hardware.

The role involves leading financial analysis for technology spend, designing data models, developing visualizations, and ensuring data quality, while collaborating with internal stakeholders across the company.

Lead the architecture and technical direction of large-scale Azure cloud infrastructure and machine learning platforms. Design distributed systems for model training, inference, data processing, and platform services; improve compute efficiency, reliability, security, scalability, and observability; guide Kubernetes and AI workloads in production; support MLOps practices; establish engineering standards; and mentor engineers across teams.

Lead the architecture, design, and implementation of core MarkLogic database features using C++. Build scalable, fault-tolerant distributed systems; optimize performance; debug complex server-side issues; and mentor engineers. Collaborate with product, development, QA, and documentation teams to deliver secure, high-quality database capabilities involving search, security, language runtimes, JavaScript integration, scalability, and reliability.

Own cross-team, platform-level engineering initiatives end-to-end: architecture, migrations, observability, on-call, and customer outcomes. Drive AI-native tooling and agentic AI adoption, mentor senior engineers, and set technical standards across teams.

Lead the architecture and evolution of managed Kubernetes and cloud-native services. Provide cross-team technical oversight, standardize platform practices, integrate open-source technologies, improve scale, performance, security, and operational efficiency, and mentor engineering teams. The role requires expertise in Kubernetes-based platforms, container runtimes, cloud-native architectures, and Go, Python, or Bash.

Lead design and implementation of complex, large-scale payment systems; drive architecture and reliability across distributed services; mentor engineers; integrate AI/ML features; collaborate with cross-functional stakeholders to deliver scalable, maintainable solutions and operational excellence.

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.

Leads architecture, design, development, and delivery of scalable enterprise applications and microservices. Drives AWS cloud-native initiatives, CI/CD automation, secure engineering practices, performance tuning, production support, and SDLC leadership. Partners with business and technology stakeholders, conducts code reviews, translates requirements into technical solutions, and mentors development teams. Uses AI-assisted development tools to improve productivity and delivery.

Principal Software Engineer serving as a technical authority for backend, data, and AI platform architecture. Responsibilities include designing large-scale distributed data platforms, streaming systems, APIs, data models, and production AI systems using LLMs, RAG, vector search, and agent orchestration. The role establishes architectural standards, governance, observability, security, and cost controls; contributes high-impact production code; guides modernization; partners with product and engineering leaders; and mentors senior engineers.

Architect and develop foundational edge-computing runtime and integration platforms for connected-home devices. Build software models for device, spatial, and occupancy data; prototype and productionize new concepts; evaluate architectures; and provide technical leadership through design reviews, coding standards, mentoring, and cross-functional collaboration. The role spans edge computing, IoT, distributed systems, embedded environments, intelligent agents, networking, and secure systems within an exploratory R&D organization.

Lead the architecture and modernization of a complex enterprise SaaS platform while remaining hands-on with critical software design and development. Define technical direction, improve scalability, reliability, security, performance, and maintainability, and guide design and code reviews. Partner across engineering and product teams, resolve complex technical challenges, establish engineering standards, mentor engineers, and translate architectural strategy into practical delivery.

Lead the technical vision, roadmap, and development of Elasticsearch’s ES|QL analytical engine and query capabilities. Design data-intensive systems, algorithms, APIs, and compute infrastructure; research search and analytics technologies; collaborate across product and engineering teams; mentor senior engineers; and contribute hands-on modern Java development. The role requires autonomous technical leadership, expertise in database internals and analytics systems, and the ability to guide complex projects from conception through delivery.

Lead architecture and technical direction for an AI-first SaaS product (Growth Studio). Define scalable services, APIs, data flows, and AI-enabled workflows; guide integrations, run architecture/code reviews and POCs; mentor engineers; produce technical documentation; and partner with product, UX, QA, and ops to deliver reliable, secure, and maintainable platform capabilities for GovCon customers.

Set technical direction for Elastic Cloud Serverless control-plane initiatives, designing distributed systems that orchestrate projects across AWS, Google Cloud, and Azure. Lead multi-quarter, cross-team delivery; write and review Go code; improve reliability, security, and cost efficiency; investigate incidents; participate in on-call; mentor engineers; and advise product and engineering leaders on technical trade-offs and roadmap decisions.

Owns technical direction and execution for major products and systems. Designs scalable backend, frontend, API, database, and infrastructure solutions; writes production code; drives architecture decisions; resolves complex engineering problems; improves testing, security, observability, and development practices; and mentors engineers across teams. The role requires leading major initiatives from design through production in a globally distributed environment.

Design and build deterministic, low-latency control systems for quantum hardware. Develop embedded firmware, device drivers, kernel modules, and orchestration for GPUs/FPGAs. Prototype in Rust, Python, C/C++, and CUDA, and collaborate with theory, hardware, and software teams to deliver production-ready, high-throughput control pipelines.

Lead development of Elasticsearch vector similarity search capabilities, including designing algorithms and data structures, implementing features, fixing bugs, and improving code quality. Collaborate asynchronously with a globally distributed engineering team and open-source community. Serve as a subject-matter expert on vector search relevance and implementation while contributing modern Java code and guiding cross-functional initiatives autonomously.

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.

Lead the architecture and development of reliable AI-powered email applications across backend, mobile, and desktop platforms. Design APIs and workflow systems supporting orchestration, state, tool use, retries, fallbacks, and failure handling. Lead a small senior engineering team, make architectural trade-offs, mentor engineers, and establish strong production practices including observability, monitoring, testing, scalability, security, and operational excellence. Partner with ML leadership to deliver robust, high-quality product experiences.

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.

Lead technical direction and hands-on execution for major software products and systems. Design scalable architectures across backend, frontend, APIs, databases, and infrastructure; write code; drive architecture decisions; solve production issues; improve testing, security, observability, and development practices; lead critical initiatives; and mentor engineers across distributed international teams.