Top AI Automation Jobs in Austin, TX

Builds and deploys AI-enabled applications, machine learning models, data pipelines, APIs, and decision-support tools for aggregate and asphalt operations. The role optimizes plant automation, production efficiency, uptime, quality, pricing, sales processes, and costs using operational, equipment, quality, GIS, and sales data. It integrates AI with plant systems and legacy software, collaborates across operations and IT, and ensures responsible AI, cybersecurity compliance, documentation, and user adoption.

Develops, configures, tests, and supports AI solutions, workflows, integrations, and model-enabled applications. Creates technical instructions and documentation, troubleshoots and optimizes AI systems, coordinates technical tasks, and collaborates with architects, delivery leaders, project teams, and stakeholders. Requires a college degree or equivalent, three years of related experience, technical communication skills, and the ability to travel and participate in on-call availability.

Leads enterprise AI architecture and strategy across the university’s digital ecosystem. Designs scalable, secure, ethical AI, machine learning, automation, and analytics solutions integrated with enterprise platforms and data systems. Establishes AI governance, responsible AI standards, MLOps/LLMOps practices, monitoring, lifecycle management, and security controls. Partners with business, product, data, engineering, cybersecurity, and platform teams; evaluates models and vendors; guides implementations, workshops, proofs of concept, adoption initiatives, and team development.

Leads organization-wide AI/ML and automation strategy, architecture, governance, adoption, and capability development across engineering and manufacturing. Establishes reusable methods, AI-ready data systems, technology roadmaps, and responsible AI practices. Guides platform and partner selection, cloud initiatives, workforce development, and cross-functional transformation while advising senior leadership on AI investments, risks, and priorities.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Design and analyze rigorous messaging experiments using A/B testing and causal inference. Build measurement frameworks, data pipelines, dashboards, automated analyses, and scalable data solutions for messaging campaigns. Partner with CRM, Product, Algorithms, and Engineering teams to translate ambiguous business questions into actionable recommendations and experimentation standards. Support messaging strategy across channels, timing, content, targeting, and new business verticals.

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.

Leads the Finance team’s AI strategy, roadmap, governance, and implementation of AI/ML, NLP, GenAI, automation, and robotics initiatives. Partners with finance, technology, CFOs, vendors, and enterprise stakeholders to identify opportunities, deploy solutions, manage programs, measure ROI, promote adoption, and ensure ethical and regulatory compliance.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Develop AI-native industrial automation systems for real-time reasoning, optimization, autonomous operation, and continuous learning at the edge. Design distributed architectures combining generative AI, machine learning, reinforcement learning, streaming analytics, and control systems. Deploy low-latency AI on edge hardware and integrate it with robotics, sensors, controllers, and industrial infrastructure while collaborating with AI research, controls, embedded systems, and operations teams.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Build AI-powered software automating hiring, finance, capital planning, contract analysis, and operational workflows. Develop production features using LLM APIs, MCP servers, and agentic frameworks; integrate enterprise systems; transform expert processes into structured data and generated work; and collaborate directly with finance, legal, recruiting, accounting, and delivery teams. The role emphasizes autonomy, rapid execution, product judgment, and forward deployment with business experts.

Identifies business opportunities for AI and automation, gathers and documents requirements, develops business cases, supports solution design and delivery, facilitates stakeholder collaboration, assists with testing and change management, and tracks project outcomes, reporting, and benefits realization.

Build applied AI and automation solutions that transform operational workflows into secure, observable, production-ready services. Develop AI agents, orchestration workflows, APIs, integrations, evaluation frameworks, and automation infrastructure across Azure, .NET, C#, Python, React, and SQL. Improve AI quality through grounding, retrieval, evaluation, observability, and responsible AI practices. Partner with engineers, stakeholders, and end users to translate business processes into effective technical solutions.

Lead end-to-end design of AI-enabled networking experiences: convert ambiguous AI opportunities into product concepts, prototypes, and shipped features. Define AI-first interactions, data and telemetry requirements, reusable UX patterns for control and explainability, and partner with platform, engineering, and research teams to deliver trustworthy, measurable intelligence features.

Leads company-wide AI adoption, operating the AI Center of Excellence, developing champions, running cross-functional AI sprints, delivering training, managing AI tools and budgets, and measuring workflow adoption, time savings, and financial impact. The role partners with Engineering to distribute shared AI skills, evaluates vendors, reports outcomes to executives, and publishes successful use cases across departments.

Build and operate AI-powered automation, CI/CD systems, distributed services, developer tools, validation platforms, and code-intelligence capabilities. Own significant systems from architecture through production, improve engineering workflows using measurable results, scale reliable automation and delivery platforms, and integrate capabilities through APIs and MCP. Establish operational practices, participate in on-call support, conduct technical reviews, mentor engineers, and lead cross-team delivery of dependable engineering platforms.

Design, build, and operate AI-powered automation, CI/CD systems, distributed services, developer tooling, and code-intelligence platforms. Own significant capabilities from architecture through production, improve engineering workflows using measurable evaluations, scale reliable automation and delivery systems, and operate secure multitenant services. Lead technical reviews, define reliability practices, integrate platforms through APIs and MCP, mentor engineers, and drive ambiguous technical problems to dependable production outcomes.

Leads enterprise AI and intelligent automation strategy, including Generative AI, machine learning, and RPA initiatives. Manages a multidisciplinary IT team, budgets, vendors, governance, project portfolios, and end-to-end solution delivery. Partners with business and technology leaders to identify automation opportunities, develop business cases, ensure compliance and security, and deliver scalable solutions with measurable business value. The role is hybrid in Camden, New Jersey, with 15% domestic and international travel.

Architect and build production agentic AI systems for customer support and compliance automation. Lead technical direction for distributed systems, APIs, orchestration frameworks, guardrails, and evaluation systems. Create reusable automation primitives, improve grounding and reliability, reduce hallucinations, and mentor engineers on LLM application design and production readiness. Collaborate cross-functionally to scale AI automation across Coinbase.

Design, develop, test, deploy, and maintain UiPath RPA solutions enhanced with agentic AI. Analyze business processes, gather requirements, document workflows, integrate systems, monitor automated processes, troubleshoot issues, and optimize solutions. Provide user training and support while collaborating with stakeholders and recommending AI and automation best practices.

Ph.D. interns apply machine learning and AI to semiconductor chip design or enterprise engineering tools. Responsibilities include developing ML models for EDA automation, placement, timing, power, and verification, or deploying LLM, RAG, and agentic systems. Interns will train, evaluate, and deploy models, conduct rigorous experiments, collaborate with engineering and technology stakeholders, assess production performance and safety, and present findings to leadership. The role requires doctoral research in AI, machine learning, computer science, electrical engineering, data science, or a related field.

Build and scale agentic AI systems that automate customer experience workflows across Slack and Salesforce. Analyze transcripts, detect SLA risks and escalations, provide self-service operational insights, and develop AI memory architecture. Partner with data, QA, workforce management, and customer advocacy teams to ensure system accuracy, reliability, trustworthy outputs, and measurable operational impact. Productize internal tools and design human escalation patterns for scalable deployment.

Build and operate an AI-driven global sourcing platform covering web crawling, data ingestion, normalization, entity resolution, product matching, provenance, and source monitoring. Integrate Zoho CRM and QuickBooks, apply LLMs with structured evaluation and human review, and identify automation opportunities across business departments. Lead pilots, train employees, measure impact, and scale the platform to hundreds of sources.

Leads enterprise AI transformation by developing the AI roadmap, prioritizing investments, managing initiative portfolios, and delivering measurable business value. Partners with executives and cross-functional teams to redesign operations, establish governance, evaluate technologies and vendors, drive adoption, and lead workforce change. Accountabilities include revenue growth, productivity, efficiency, customer experience, compliance, AI maturity, and value realization.