Top AI Specialist Jobs in Austin, TX

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

Evaluate and implement AI and automation solutions for legal workflows; lead pilots and rollouts; collaborate with attorneys and tech teams; create training and change management materials; identify process improvements to increase efficiency across practice areas.

Design, research, and deploy NLP/GenAI surveillance models (LLMs, RAG, knowledge graphs) to detect suspicious financial behavior; build production-ready systems, collaborate with Compliance/Legal/IT, and drive adoption of AI solutions.

Annotate and review large volumes of image, video, infrared, and sensor data to support maritime perception models. Identify vessels, objects, and environmental features; apply evolving labeling guidelines; perform manual annotation and quality review of auto-labeled data; escalate edge cases and meet project deadlines while maintaining accuracy and consistency.

Lead design of AI-enabled capabilities for Amazon Connect contact centers: run AI discovery workshops, define LLM and agentic AI solution architectures, assess data and knowledge readiness for RAG, create implementation roadmaps, design customer and agent experiences, partner with platform and engineering teams, and provide responsible AI guidance and governance for contact center solutions.

Serve as an AI technical consultant in pre-sales and early post-sale: prospect accounts, lead technical discovery, build AI agents and POCs with Datagrid, design demos, translate requirements into implementation plans, and advise sales on strategy.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Design and deploy production ML/AI architectures on the Databricks platform, lead Generative AI (LLM, RAG, agent) implementations, optimize and scale MLOps pipelines, provide technical pre-sales support, and translate customer feedback into product improvements while mentoring peers and meeting delivery milestones.

Review, localize, fact-check, translate, and adapt football-related content (EN→FR-CA). Conduct market research on terminology and trends, provide copy-editing and feedback, and evaluate/MTPE machine translations to ensure native-level quality and adherence to style guides.

Review, localize, translate, fact-check, and adapt football-related content from English (US) to Dutch, following style guides. Perform quality control, MT post-editing and evaluations, conduct market-specific research, and provide feedback to improve localized content for Dutch audiences.

Review, localize, fact-check, translate, and adapt football-related content for Croatian audiences; perform MT post-editing and quality control; conduct market-specific research on terminology and trends; provide feedback and adhere to style guides.

Design, deploy, and operate a secure, scalable Generative AI platform on AWS (Bedrock) for production LLM applications. Own architecture, deployment, monitoring, incident management, reliability, governance, and cost optimization in regulated financial environments.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) for production LLM applications in regulated environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and cost optimization. Implement RAG, Agents, inference, guardrails, observability, access controls, and governance, with emphasis on Responsible AI and production reliability in financial services.

Design, build, and operate a secure, scalable enterprise Generative AI platform on AWS (including AWS Bedrock). Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and governance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Support production-grade GenAI applications in regulated/financial environments.

The AI Data Specialist role involves data collection, evaluation, annotation, pairwise comparisons, and tagging across various content types.

The role involves designing and delivering AI training programs, creating learning materials, and facilitating workshops to enhance user understanding of AI tools within enterprises.

Lead sales and deployment of custom AI/ML solutions, driving pipeline and revenue for allocated accounts. Collaborate with Field Sales, Product, Sales Engineering and AI teams to discover requirements, architect agentic AI solutions, write SOWs, negotiate commercial terms, and manage complex sales cycles to ensure customer adoption and measurable business outcomes.

Design, develop, and deploy Agentforce AI agents and custom actions on the Salesforce platform. Build Apex classes, LWCs, flows, and API integrations with Data Cloud and legacy federal systems. Enforce AI safety, federal security/compliance, support testing/UAT, and enable secure DevSecOps/CI/CD deployments in cleared environments.

Design, develop, and deploy Agentforce AI agents and custom actions on Salesforce. Build Apex, LWCs, flows, and secure API integrations with legacy federal systems and Data Cloud. Ensure AI safety, compliance, testing, and support CI/CD/DevSecOps practices in cleared federal environments.

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.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Create, optimize, schedule, and publish blog and social content about AI applications. Test headlines, landing pages, and ads; review analytics, predict opens/clicks/conversions, write performance reports, and personalize curated content.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.