Top AI Automation Jobs in Austin, TX

Design and build AI-enabled automation and ML workflows to accelerate validation, debug, and performance optimization of high-power semiconductor power solutions. Create automated infrastructure, support HW/FW/SW teams, and produce end-user collateral to improve engineering efficiency.

Lead strategic customer co-innovation engagements for AI and autonomy. Manage executive briefings, define/govern co-innovation frameworks, track milestones and commercial impact, capture insights for productization and sales enablement, and convert outcomes into event and marketing content.

Lead development of AI-driven solutions for timing and constraint analysis in EDA, integrating data sources and creating autonomous analysis agents.

Lead enterprise adoption of Microsoft Copilot, Copilot Studio, and Power Platform by analyzing business processes, designing AI agents, building ROI-backed automation roadmaps, delivering training and prompt engineering best practices, and measuring utilization and productivity improvements across functions.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

Build AI-powered workflows, agents, and integrations to automate marketing research, creative asset preparation, campaign analysis, reporting, and internal coordination. Prototype and productionize LLM-based tools, connect data sources and ad platforms, validate automation quality with real use cases, and document systems for reuse and scaling.

Build and maintain internal and customer-facing web/cloud apps and AI automations. Integrate with third-party APIs (QuickBooks, Microsoft Graph, Zoho, Zoom), implement generative-AI features, ensure security, deploy to cloud, and collaborate with leadership and IT. Work independently on design, testing, and maintenance across varied projects.

Build and ship AI-driven automation across the go-to-market lifecycle: prospecting, lead routing, deal support, retention, and instrumentation. Design agents and workflows, connect GTM systems and data, deploy and monitor production AI, set guardrails and evals, and partner with Sales, Solutions Architecture, Marketing, and RevOps to measure and improve impact.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.

Design and build automation frameworks and evaluation pipelines for agentic AI products. Develop non-deterministic tests, golden datasets, tool-use validation, prompt regression tests, latency/token monitoring, hallucination detection, and collaborate with AI engineers to convert requirements into measurable automated test cases.

Lead QA Automation for agentic AI products by designing eval pipelines, golden datasets, and automated tests for tool-use, hallucination detection, latency/token monitoring, and regression across models and prompts. Integrate performance testing into CI/CD and collaborate with AI engineers to convert requirements into measurable automated evaluations.

Responsible for building tools and frameworks to scale AI and ML capabilities through automation, enhancing the speed and consistency of analytics delivery.

Lead AI and sales automation product efforts for Salesforce: translate business needs into Jira stories, design automations and integrations, coordinate UAT, consolidate data sources, and build AI-driven solutions to reduce manual CRM administration. Occasional hands-on scripting for simple automations.

You will build AI-native creative workflows, generate production-grade assets, and establish automation systems for creative processes across multiple brands.

Build and maintain LLM-powered agents and automation pipelines to create, review, and publish educational content. Integrate and optimize Skilljar and Sanity CMS, eliminate content ops bottlenecks, partner cross-functionally, and implement interactive learning components to scale personalized learning.

Design and build AI-powered automation workflows and integrations for Pragmatico and clients. Lead discovery, architect solutions using LLM APIs and integration platforms (Zapier/Make.com), present solutions to stakeholders, train client teams, and create reusable automation frameworks and thought leadership content.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Design, build, and scale AI-powered automation using LLMs, RAG, vector DBs, prompt pipelines, and agent systems. Integrate with internal tools and cloud platforms, implement orchestration, observability, security guardrails, measure impact, and partner cross-functionally to replace manual processes with reliable production-grade automation.

Lead enterprise AI and automation strategy, governance, and delivery. Partner with business and IT teams to identify high-value use cases, build production-ready AI solutions, establish repeatable implementation patterns, ensure security and compliance, measure business impact, and enable adoption through mentoring and standards.

Pre-sales technical architect advising on Microsoft Copilot and Power Platform adoption. Engage executives, run workshops, design and deploy custom Copilot agents, build prototypes and integrations, and develop automation using Power Automate/Power Apps/Power BI while guiding change management and governance.

The AI Automation Engineer will apply AI in finance operations to automate processes like AP, AR, and reconciliation, ensuring compliance and performance measurement.

Lead AI-driven reconciliation and automation to improve encounter data quality. Own model performance, identify root causes, partner with technical and business teams to enhance models, prioritize roadmap, and scale automation while communicating results to stakeholders.

The role focuses on AI applied engineering, integrating AI into existing workflows, building automation and tools, and improving team efficiency. It requires strong engineering skills and an understanding of user workflows.

Lead the design and implementation of AI agents and automation across pro-code and no-code platforms. Define repeatable automation patterns, integrate AI platforms with business tools via APIs, build RAG pipelines and vector DB integrations, write Python scripts for complex integrations, and guide technical decisions while working closely with the VP of AI to review agent performance and scale solutions.

The Director of AI Automation leads AI-driven automation systems, translating strategic goals into practical solutions, managing teams, and enhancing operational efficiency.