Top AI Ethics Jobs in Austin, TX

Design, implement, and evaluate applied research projects to improve alignment, safety, and evaluation of LLM-based guardrails. Work on experiments (e.g., synthetic data quality metrics, explanations for blocked content), deliver results with mentor guidance, and present findings to the team to shape product capabilities.

Lead development and oversight of AI governance frameworks, policies, controls, and risk/compliance practices. Partner with business, delivery, and technical teams to align governance with project delivery, support SDLC-based project governance, recommend improvements, and communicate governance expectations across the organization.

Design and review consulting-style prompts, structured answers, and evaluation criteria to benchmark AI outputs against consulting frameworks. Provide structured feedback on clarity, logic, and business rigor. Conduct online research and synthesize insights to support evaluations and improve model alignment. Work remotely as an independent contractor on a flexible, part-time engagement.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

Lead enterprise adoption of AI by translating strategy into an executable roadmap, building governance and operating models, driving cross-functional program execution, defining success metrics and business cases, and advising executives to ensure responsible, measurable AI impact across clinical and operational domains.

Lead content and strategy for a 12+ event annual portfolio: design agendas, curate speakers and attendees, own pre-event framing and speaker engagement, produce written outputs, steward post-event continuity and community building, manage stakeholder relationships across AI safety, and collaborate with internal teams to translate event visions into participant-facing programs and systems.

Lead design and delivery of enterprise analytics and AI governance frameworks, operating models, CoEs, and maturity assessments. Advise on Responsible AI, generative AI governance, adoption strategies, change management, and stakeholder alignment. Create reusable methodologies, run workshops, assess maturity, and mentor consultants to scale trusted analytics, automation, and AI across large organizations.

The Director of Artificial Intelligence will define, lead, and implement AI strategies, managing R&D, building teams, and ensuring ethical AI use to drive business outcomes.

Lead internal AI product strategy and operating model: set priorities for knowledge/context layers, reusable skills/agents, governance and trust, adoption and L&D strategy, partner with engineering, security, legal, and stakeholders to scale safe, company-wide AI practices and measure impact.

Own security and compliance for the Enterprise AI program by building security tooling, policy-as-code guardrails, reusable secure AI components, and observability to detect anomalous model behavior while partnering with Cyber Security and delivery teams.