Top Tech Jobs & Startup Jobs in Austin, TX

Leads global talent acquisition operations and enablement by modernizing recruiting systems, implementing structured assessments, improving workflows and governance, and developing reporting and automation. Partners with cross-functional stakeholders to improve recruiter efficiency, hiring quality, and candidate experience. Manages TA vendors, oversees integrations, establishes SOPs, audits data, and leads a high-performing talent acquisition operations team.

Lead the architecture, development, optimization, and operation of production LLM and AI automation systems. Design capabilities including agents, retrieval, code generation, tool use, model routing, evaluation, and observability. Drive platform modernization, scalability, reliability, architecture, and code quality while mentoring engineers and influencing technical practices across teams. Build prototypes, establish engineering standards, conduct reviews, and communicate complex technical concepts through documentation and cross-functional collaboration.

Lead the design and development of production AI systems for enterprise application automation. Responsibilities include building reliable agents and orchestration, extracting specifications from existing systems, modeling application intelligence and retrieval, developing evaluation and CI pipelines, optimizing reliability and scale, using AI coding tools, mentoring engineers, and documenting technical practices.

Lead the architecture, development, modernization, performance optimization, and reliability of enterprise-scale machine learning platform software. Mentor engineers, influence cross-team technical decisions, conduct code reviews, evaluate AI-assisted code, design cloud-native systems, and drive high-quality delivery across complex application layers. The role requires expertise in distributed systems, cloud infrastructure, production services, and enterprise engineering practices.

Build and optimize developer-facing tools, including IDE integrations, CLIs, code-analysis systems, and CI/CD workflows. Integrate transparent, reliable AI capabilities into developer experiences, optimize high-volume production services, and improve availability, latency, and efficiency. Drive engineering best practices through code reviews, automation, documentation, and technical leadership while mentoring junior engineers. The role also requires communicating complex architectures and operating tooling across enterprise deployment environments.