Top AI Jobs in Austin, TX

Lead the identification, design, and delivery of AI-driven automation within Customer Operations. Translate operational pain points into scalable solutions, evaluate tools, run end-to-end implementations, partner cross-functionally, measure outcomes, and enable adoption to improve efficiency and customer experience.

Lead end-to-end delivery of AI and ML services within Managed Services. Manage project planning, budgeting, execution, and quality. Mentor and develop team members, cultivate client relationships, implement model monitoring and operationalization practices, and collaborate with architects and engineers to ensure compliant, reusable AI solutions.

Lead AI strategy, partner engagements, and operational execution across CrowdStrike products. Align R&D and product delivery to company AI strategy, prioritize initiatives, set organizational goals, drive thought leadership, and create order in complex cybersecurity AI environments while delivering customer value.

As AI Enablement Services Lead, you will design AI solutions for operational tasks, automation of delivery processes, and enhance team capabilities in utilizing AI effectively.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Lead design, launch, and lifecycle management of Pluralsight solutions (AI, Cloud, Security). Define expert POV, build curricula, labs, assessments, and blended learning programs. Own roadmap, metrics, GTM partnership with Sales and Marketing, and continuous iteration using data and SME collaboration to drive enterprise customer outcomes.

Lead and grow an AI Platform Enablement team to build a governed internal AI development environment. Define platform strategy, partner with security and infrastructure, drive adoption via enablement programs, and establish metrics for usage, onboarding, and control effectiveness. Act as an executive-facing leader delivering secure, scalable platforms and change management.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Own and evolve Sonar's AI-native internal platform: design, build, and operationalize agent/connector integrations (Claude/MCP, Rovo), administer and productize Jira Service Management and Atlassian Cloud, implement scalable automations and integrations, maintain CMDB/assets, enforce ITSM/ITIL processes, support security/compliance audits, and partner across teams to drive platform roadmap and stakeholder enablement.

Lead enterprise AI transformation and architecture engagements from strategy through delivery. Advise executives on AI roadmaps, design end-to-end AI and data architectures (including knowledge graphs, data catalogs, RAG, and integrations), establish governance and responsible AI practices, drive adoption and change management, and develop reusable practice assets and thought leadership to realize business value.

Design, build, and operate AI agents and decision-support systems embedded in GTM workflows. Conduct stakeholder research, prioritize problems, ship and iterate on agent outputs, monitor adoption and quality, and scale reusable solutions across sales and customer-success motions while staying closely embedded with field teams.

Architect, build, and operate an internal AI platform that enables agentic use cases and safe model access. Own platform APIs, SDKs, LLM gateway, provisioning, access governance, license hygiene, observability, and runbooks. Implement AI protocols (MCP, A2A, ARD), enforce identity and policy-as-code controls, strengthen AWS infrastructure (Bedrock, IAM, network security), and partner cross-functionally to drive platform standards and operational excellence.

Lead end-to-end development and scaling of AI/LLM solutions for marketing operations, including RAG applications, copilots, automation, production deployment, monitoring, and governance. Partner with cross-functional teams to build reusable frameworks, demonstrate measurable impact, and drive enterprise AI adoption.

Design and deliver enterprise-grade AI workflow transformations on GCP. Build secure, event-driven backend services and multi-step AI agents, integrate bots with enterprise systems, implement telemetry, testing, CI/CD, HITL validation, and create reusable architecture, documentation, and runbooks while guiding adoption and governance.

Design, build, and scale AI-enabled workflow and automation solutions across collaboration platforms and enterprise systems. Translate manual processes into secure, reusable, event-driven automations using Python/JavaScript, integrate AI capabilities like Gemini, implement logging and telemetry, and partner with product, security, and business teams to deploy and sustain enterprise transformation solutions.

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.

Design, build, and operate low-latency, cloud-native AI-powered fraud decisioning and automated remediation systems. Implement AI-assisted SDLC and agentic multi-agent workflows, modernize streaming/data pipelines and microservices, ensure observability/SLOs/security, evaluate vendor solutions, and mentor engineers.

Design, implement, and deploy end-to-end ML models and data pipelines for ranking, recommendations, search, and personalization. Build scalable data quality checks, monitoring, and evaluation (A/B tests, offline/online) to ensure reliable, fair, production-grade AI. Collaborate with product, analytics, and engineering to translate business needs into ML solutions and drive iterative improvements.

Build production AI-powered analytics and natural-language intelligence on governed telematics, aftersales, and energy data. Design multi-agent systems, retrieval/grounding/reasoning/memory patterns, and reusable AI services. Partner with data product teams to ensure trust, explainability, scalability, and performance of AI experiences for enterprise users.

Design and build a global, serverless AI inference platform running on heterogeneous GPUs and accelerators. Optimize model scheduling, request routing, caching, and load balancing for low latency. Improve reliability and observability, lead cross-functional projects, and mentor junior engineers.

The Principal AI Compiler Engineer designs hardware for AI, ensuring models translate effectively to silicon and perform optimally in 5G applications.

The Principal AI Model Architect's role includes optimizing model architectures for new hardware, translating AI algorithms into hardware specifications, and projecting performance for silicon design.

Lead and define AI architecture, ensuring scalable, reliable AI systems while mentoring engineers and collaborating with product teams.

Lead strategy and roadmap for CrowdStrike's Charlotte GenAI platform, deliver developer-first AI capabilities, partner with engineering and data science, drive cross-functional delivery and adoption, evangelize GenAI across the Falcon ecosystem, and ensure platform scalability, performance, and security.

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