Top AI Specialist Jobs in Austin, TX

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

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.

Join an internal AI enablement team to assess workflows, build prompt-based automations and lightweight apps, coach business teams, test and document tools, track user skill development, research AI platforms, and ensure governance and security compliance.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

Develop and optimize prompts, context management, and multimodal prompting workflows for LLM-powered products. Collaborate with Customer Success to iterate on prompts, review conversations and feedback, document and teach prompting best practices, and build small prototypes using Python and low-code tools to test complex prompting and data workflows.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead discovery and build AI-enabled operational workflows across R&D and business functions. Translate requirements into practical solutions, own design-to-launch, optimize adoption, and manage Marketing Operations (campaigns, automation, tech stack). Measure outcomes, document solutions, and ensure alignment with shared AI standards.

The SAP AI Specialist will integrate AI within SAP systems, optimizing capabilities using SAP Joule and BTP AI services, and developing predictive analytics and automation solutions.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Lead change management for AI-powered tools and workflows: assess impacts, build adoption plans, create training and communications, coach leaders and enablement teams, recruit change champions, track adoption metrics, and share learnings across the Change Management team.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.

Evaluate and improve LLM financial reasoning by designing real-world finance tasks, creating reference solutions, scoring AI outputs with structured rubrics, refining evaluation frameworks, and collaborating with researchers to raise data quality and model performance. Must provide detailed feedback and identify gaps to enhance AI across finance use cases.

The AI Implementation Specialist analyzes client workflows, identifies automation opportunities, designs and implements AI-driven solutions to enhance business efficiency and productivity.

Design and deliver GenAI solutions: prototype to production LLM services, build RAG pipelines, fine-tune models (LoRA/QLoRA/PEFT), engineer prompts/tools/memory, ensure safety and evaluation, deploy with MLOps (CI/CD, containers, IaC), optimize inference, and ensure security/compliance while collaborating with product, data, and SRE teams.

Design realistic, specialty-specific clinical case scenarios and gold-standard attending-level responses, evaluate and grade AI-generated outputs using structured rubrics, provide detailed written feedback to improve model clinical reasoning, and participate in onboarding, calibration, and review sessions in a fully remote, asynchronous contractor role (~20 hours/week).

PhD-level physicists will design challenging graduate-level physics problems and contribute high-quality datasets to improve AI model reasoning, ensuring scientific rigor and consistency while collaborating remotely and asynchronously.

Lead design, validation, and continuous improvement of AI-assisted measurement and learning systems for K-12 assessments. Translate measurement intent into reproducible AI workflows, prototype AI-assisted content generation, ensure outputs meet validity, fairness, accessibility, and instructional standards, design validation and monitoring frameworks, partner with cross-functional teams (AI Science, Technology, Content), and contribute research, documentation, and thought leadership on intelligent assessment and learning systems.

The AI Operations Specialist will support CoinMarketCap's AI team by conducting feature evaluations, developing tools and automations, managing outreach, and collaborating with internal stakeholders to enhance AI operations.

Design, build, and deploy production AI systems and integrations (LLM-based) for law-firm clients. Create connectors, automation workflows, agents, and enablement programs, embed AI into client processes, and support internal AI adoption.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Design, build, and operate a secure, scalable GenAI platform on AWS (including Bedrock). Own platform lifecycle, enable LLM inference, RAG, Agents and guardrails, ensure observability, incident management, security, compliance, cost optimization, and reliability for production-grade regulated-financial environments. Provide Python-based development and support for microservices and REST APIs.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Own strategy, design, and optimization of Vanta's customer-facing chatbot and internal AI Copilot. Build and maintain AI-driven knowledge, design conversation flows in Intercom, analyze performance data, and collaborate cross-functionally to increase resolution rates and CSAT. Handle a small volume of support tickets to inform improvements and maintain product expertise.