Top Tech Jobs & Startup Jobs in Austin, TX

Defines the architecture and roadmap for shared test automation frameworks validating AI hardware platforms. Develops scalable test components, automated suites, CI/CD integrations, data pipelines, and observability tools. Leads cross-layer debugging across software, firmware, hardware, and lab infrastructure; improves test reliability, speed, and reproducibility. Partners with cross-functional engineering and manufacturing teams, establishes standards, mentors engineers, reviews designs and code, and provides Principal-level technical direction.

Provides technical leadership for mechanical infrastructure supporting high-performance computing data centers. Owns design standards, reviews HVAC and cooling systems, coordinates multidisciplinary interfaces, directs consultants and suppliers, evaluates reliability and efficiency, and supports inspections, commissioning, factory acceptance testing, and operational handover. Guides engineers and assesses emerging cooling and heat-rejection technologies for future deployments.

Design, develop, and deploy UEFI firmware for hyperscale AI server platforms. Responsibilities include platform initialization, hardware configuration, security features, RAS capabilities, telemetry, firmware updates, CI/CD integration, and system management interfaces. The role partners with hardware, silicon, BMC, ODM, security, and validation teams, while debugging firmware and hardware issues across laboratory and production environments.

Develop and extend low-level diagnostic and stress-testing software for next-generation AI SoCs. Build configurable validation tools covering CPUs, accelerators, memory, storage, PCIe, firmware, BMC, and other platform components. Diagnose hardware, firmware, operating system, and driver interactions; expose intermittent failures such as silent data corruption and timing issues; automate validation across server and rack-scale environments; and improve observability, fault isolation, and silicon bring-up through collaboration with hardware, firmware, and validation teams.

Develop system-level diagnostics, stress-testing software, and validation utilities for next-generation AI SoCs. The role involves extending Arm diagnostics, testing CPUs, memory, PCIe, storage, firmware, and accelerators, debugging hardware-software interactions, automating validation across platforms, analyzing failures, and improving observability and fault isolation. Collaboration with hardware, firmware, software, and validation teams is central to supporting silicon bring-up and platform reliability.

Validate signal and power integrity for advanced compute platforms through hands-on measurement, electrical compliance testing, troubleshooting, and simulation correlation. Develop measurement plans and fixtures, measure high-speed interconnect performance, perform calibration and de-embedding, correlate results with simulations, collaborate with silicon, package, board, system, and vendor teams, and produce validation and compliance reports.

Analyze and optimize AI training and inference workloads across distributed systems. Design benchmarks, profile performance, identify bottlenecks, and optimize communication software using MPI, NCCL, UCX, libfabric, and RDMA. Translate modeling and benchmarking results into validated system improvements while coordinating technical work across hardware, software, networking, and architecture teams.

Lead performance strategy for large-scale AI training and inference systems. Investigate workload behavior, profiling, benchmarking, modeling, distributed communication, and multi-node scaling across hardware and software. Define measurement standards, guide optimization roadmaps, review C++ and Python tools, and influence system architecture and engineering priorities across teams.

Lead a multi-site team responsible for functional post-silicon validation of AI SoCs and platforms. Plan and debug bare-metal C/C++ tests, deploy validation on first silicon, build Python automation and regression frameworks, analyze failures, improve test infrastructure, collaborate across hardware, firmware, software, and systems teams, and provide technical guidance and feedback to architects.

Lead post-silicon validation of advanced AI chips and platforms, including bare-metal C/C++ test development, first-silicon bring-up, debugging, and Python-based automated regression frameworks. Analyze failures, improve validation infrastructure and methodologies, collaborate across engineering teams, provide architectural feedback, and mentor engineers. Support software, firmware, production test, characterization, and new product introduction activities.