Top AI Jobs in Austin, TX

Lead design and deployment of enterprise-scale multi-agent AI systems across the semiconductor lifecycle. Define strategy, architect agentic AI platforms (LLMs, RAG, knowledge graphs), identify automation opportunities, establish AI governance, integrate with EDA and operations systems, mentor technical leaders, and represent the company externally.

As an Associate Technical Onboarding Manager, you will manage the onboarding process for new customers, gather technical requirements, and ensure quality customer experience through project management.

Lead product management and program delivery for enterprise software implementations. Manage product lifecycle, stakeholder relationships, reporting, risk, and financial tracking; mentor juniors and align project objectives with strategic goals.

Use advanced analytics, statistical techniques, and machine learning to extract insights from large datasets. Design data solutions and pipelines, build predictive models (R, MATLAB), and apply TensorFlow and Scikit-Learn for deep learning and NLP. Collaborate with teams and clients, deliver quality work, and adhere to firm standards.

The Principal Edge AI Firmware Engineer will develop and optimize embedded software for AI applications, focusing on performance and energy efficiency. Responsibilities include enhancing AI runtimes, profiling tools, and ensuring customer integration across embedded environments.

Lead AI agent build and DevOps workstreams within a Data & Analytics practice. Develop and implement BI and cloud analytics solutions, build visualizations (QlikView, Spotfire), validate data integrity, manage client relationships, identify optimization opportunities, and mentor teams to ensure project delivery and performance.

Lead managed-services teams to design and deliver AI agent builds and DevOps-enabled analytics solutions. Develop data architecture, advanced analytics and visualizations, ensure data integrity/security, manage client accounts, mentor staff, and drive continuous improvement to generate strategic insights and business value.

As a Sr. AI Solutions Engineer, you will develop AI solutions, prototype applications, teach teams, and drive AI adoption across the company.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

Lead the creation of innovative AI solutions for healthcare systems, serve as a trusted advisor, foster collaboration, and drive operational excellence while managing complex challenges in healthcare AI.

As a Senior Manager in Data and Analytics Engineering at PwC, you'll design data architecture strategies for healthcare, mentor teams, influence stakeholders, and enhance healthcare operations through data solutions.

12-week on-site internship supporting Professional Services Revenue organization by applying project management and AI/no-code tools to map, document, prioritize, and automate sales/RevOps processes. Responsibilities include project coordination, process playbooks, AI use-case research, tech-stack evaluation, prototyping with IT/engineering, and delivering measurable recommendations.

Lead design and delivery of production-grade AI capabilities to improve developer productivity across engineering tools, CI/CD, and embedded software workflows. Define technical vision, integrate AI into toolchains, drive productionization, establish responsible AI standards, mentor engineers, and influence cross-functional roadmaps and implementations.

Lead research into vulnerabilities and defenses for LLMs and agentic systems. Perform deep-dive analysis of prompt injection, RAG pipelines, tool integrations, and autonomous agent security; map findings to industry frameworks; develop testing methodologies and publish thought leadership.

This role involves developing and implementing testing frameworks for ensuring reliability and performance of AI security controls across platforms. The engineer will expand test coverage and contribute to quality metrics for AI models.

The Senior Backend Engineer will design, build, and scale AI-driven operations, manage the product lifecycle, and implement AI technologies while ensuring data security and system performance.

The Senior Software Engineer will develop AI-enabled applications, optimize data workflows, mentor engineers, and ensure software quality and performance.

The role involves developing partnerships with global firms to integrate ServiceNow's AI platform, driving business growth and customer adoption through strategic collaboration and pipeline creation.

The Professor will teach undergraduate STEM courses, mentor students, advance UATX's mission, and contribute to maintaining a rich intellectual environment.

The Senior Software Engineer for Support AI will develop voice and chat systems for customer support, driving projects from concept to production, while collaborating across teams and improving AI capabilities through integration and data insights.

Lead design and deployment of AI agents and workflow automations across Supply & Operations, coach and lead Operational Excellence (Lean/Six Sigma) projects, build OE capabilities, embed continuous improvement and AI-driven workflows into enterprise systems, and lead global OE programs and strategies in External Supply.

Lead product marketing for AI and quality engineering offerings: develop persona-based positioning, create content across the sales lifecycle, support demand generation, conduct market and competitive research, influence product roadmap, run win/loss analysis, and represent the company externally to drive pipeline and adoption.

As a Senior AI/ML Engineer, you'll enhance developer productivity by leading CI solutions, mentoring engineers, and implementing scalable systems.

Lead discovery and delivery of AI-first AEC product capabilities. Define roadmap, prototype agentic LLM workflows, translate research into requirements, measure outcomes, and partner with UX, Engineering, and GTM to drive adoption and growth.