Top Tech Jobs & Startup Jobs in Austin, TX

Provides empathetic, efficient customer support across multiple channels; documents interactions in CRM software; analyzes issues and proposes solutions; applies product knowledge to educate users; shares customer feedback and sentiment trends; develops support documentation; and supplies scenario-based input to train AI systems. Requires at least three years of professional customer support experience, strong communication and problem-solving skills, CRM proficiency, and experience managing complex cases.

Provide subject-matter input on criminal law to train AI: review and analyze court filings and case materials, draft and annotate scenarios, evaluate AI outputs for legal accuracy and ethics, flag nuanced issues, and collaborate remotely to deliver actionable feedback while staying current on statutes and case law.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Analyze computer systems and business processes, gather and validate stakeholder requirements, create BPMN/UML process models, use SQL for data analysis and troubleshooting, and collaborate remotely on customer projects. The role also contributes domain expertise to AI training data and scenario validation.

Contract remote role for US-based attorneys with mandatory Vault Law 100 firm experience. Perform legal research, analysis, drafting, document review, quality assurance, and collaborative remote work to produce high-quality legal content and feedback across varied U.S. law topics.

Develop and maintain scalable Java backend systems using Spring Boot and microservices architecture. Collaborate with customer teams, review specifications, write clean code, participate in code reviews, document solutions, and troubleshoot and optimize backend performance, reliability, and security. The role also contributes technical expertise to training next-generation AI systems, though prior AI experience is not required.

Build reinforcement learning environments to evaluate AI systems on software engineering tasks involving MCP tools. Responsibilities include creating reproducible environments, deterministic verification, golden reference solutions, bug fixes, feature development, codebase refactoring, and performance optimization. The role is remote, flexible, contract-based, and output-focused, with no prior AI experience required.

Interpret U.S. sales and use tax statutes and regulations across multiple jurisdictions, create precise legal rubrics for AI tax translations, evaluate outputs against statutory requirements, and write test scenarios covering conditions, exceptions, thresholds, ambiguities, and edge cases. Submit structured evaluations through a digital review platform.

Reviews and refines AI-generated content and data outputs, develops prompts, evaluates model performance using rubrics, conducts independent research and fact-checking, annotates data, and summarizes complex findings in technical reports. Works asynchronously with project leads and domain experts to improve AI output quality and analytical standards.

Identify companies with valuable operational data for AI training and evaluation, conduct outbound prospecting, run discovery calls, explain data partnership value and technical concepts, address privacy and ownership concerns, negotiate terms, close B2B deals, manage the sales pipeline, and coordinate partner onboarding with internal teams.