Top AI Automation Jobs in Austin, TX

Work with business system analysts and developers to design, build, and deploy AI agents, copilots, and automation integrated with enterprise systems. Develop reusable agent skills, connect agents via MCP to enterprise tools and data, advance spec-driven development, and implement safety/observability guardrails for production in a defense environment.

The AI Automation Engineer develops AI-driven systems to automate sales and marketing workflows, partnering with various teams to enhance revenue generation and process efficiency.

Lead enterprise AI product strategy, governance, and adoption for internal platforms and employee tooling. Prioritize high-value AI and automation use cases, run pilots, evaluate vendors, define FRDs/TRDs, manage delivery (QA/UAT, deployments, hypercare), and drive change management and metrics reporting to deliver measurable business value in a regulated fintech environment.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

As a Staff AI Engineer, you will design and implement AI-powered automation for internal departments, manage the full project lifecycle, and enhance various processes across CargoSprint, focusing on business impact and collaboration.

Develop and manage intelligent automation solutions using UiPath, bridging communication between project managers and clients, conducting process analysis, and providing documentation.

Partner with business leaders to discover, prioritize, and design AI and automation solutions. Elicit and document functional, non-functional, and data requirements; create user stories and acceptance criteria; oversee implementation, UAT, and adoption; ensure governance, responsible AI practices, and measurable value realization while optimizing processes and driving change management.

Design and execute test strategies and automation for cloud-native and GenAI/AI-ML systems. Perform functional, integration, performance, security, and API testing; validate model accuracy, fairness, robustness, and data quality; integrate automation into CI/CD; track defects; mentor junior QA engineers.