Top AI Automation Jobs in Austin, TX

As a Principal AI Transformation Consultant, you will partner with AE firms to identify workflows for AI enhancements, lead discovery sessions, design transformation plans, and drive successful adoption of Champ for ERP, focusing on measurable outcomes and behavioral change.

The Senior Technical Product Manager leads the development of AI-enabled digital products, collaborating with stakeholders and managing the product lifecycle to drive business results.

Lead client engagements in insurance data, analytics, and AI: define roadmaps, run discovery sessions, design solutions, manage delivery and teams, develop proposals, and ensure DataOps, cloud (AWS), governance, and best practices across AI and analytics initiatives.

The Principal Consultant leads AI and digital transformation engagements, guides clients in identifying AI opportunities, builds strategies and roadmaps, implements solutions, and develops teams to achieve measurable business outcomes.

The Partner Value Solution Engineer empowers partners by providing technical guidance, developing enablement programs, and managing relationships to enhance the selling and delivering of NiCE solutions, particularly within AI and customer experience technologies.

The role leads AI adoption across business functions, prioritizing use cases, building business cases, and driving organizational change necessary for successful implementation. It requires collaboration with IT leadership and the presentation of ROI to business stakeholders.

Lead onboarding and implementation of AI solutions in banks. Manage customer transformation journeys, ensure project alignment, and facilitate engagement with stakeholders to achieve maximum ROI.

As an AI Automation Engineer, you will partner with business groups to assess challenges and deliver AI-driven automation solutions while ensuring code quality and collaborating with cross-functional teams.

Lead intake, prioritization, and stakeholder engagement for enterprise AI opportunities; translate business problems into evaluable AI use cases, align to strategy and governance, define KPIs/ROI, and coordinate with execution teams and vendors to ensure responsible, feasible AI adoption.

The SME will develop a curriculum on AI for finance, creating engaging content and videos to train finance professionals in AI applications. They must leverage their extensive finance experience and AI understanding to enhance learner success.

The GTM AI Enablement Lead will unify go-to-market strategies, design training, improve processes through AI workflows, and enhance customer experience.

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 enterprise AI-native transformation by designing and deploying multi-agent systems, agent orchestration, and RAG-based workflows. Work with executives to translate strategy into production-grade prototypes, scalable accelerators, and human-in-the-loop governance to improve portfolio management, delivery orchestration, and operational intelligence.

Lead end-to-end delivery of complex AI and data science customer engagements. Align stakeholders, design scalable ML/AI architectures, guide technical implementation across data pipelines and models, manage risks and timelines, and provide executive and technical leadership to translate technical solutions into business outcomes.

Lead a small GTM engineering team to integrate and automate Sales and Marketing systems (Salesforce, Clay, Boomi, Salesloft). Build end-to-end workflows, deploy AI/ML and LLM-powered automations, maintain data pipelines and dashboards, ensure data hygiene, and drive GTM process execution from requirements through adoption.

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

Lead development of AI-enabled automated workflows and tooling to accelerate validation, tuning, debugging, and performance optimization of Renesas power delivery solutions across HW/FW/SW teams.

The Lead Solutions Architect will drive revenue by developing tailored solutions using Sprinklr's AI platform, collaborating across teams, and leading presales activities while ensuring ethical AI use in architectures.

Lead and build AI-powered automation across Customer Operations (CX, Claims, Underwriting). Own the automation roadmap, partner with Product and Engineering, design prompt and agent architectures, drive pilots to scaled production, build executive business cases, manage vendor tooling feedback, and grow a team of builders focused on GenAI integration and workflow automation.

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.

The Senior AI Automation Engineer will lead the design, development, and delivery of scalable AI automation solutions and data infrastructure, aiming to transform HackerOne into an AI-first organization.

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.