Top Generative AI Jobs in Austin, TX

Own and improve the AI Social render pipeline and agent loops that generate on-brand Instagram carousels and reels. Build prompts, structured outputs, tool-calling, and media composition to ship high-quality generative image, video, voice, and music products in collaboration with product, design, and content strategy.

Embed with client engineering teams to operationalize LLMs and retrieval systems across multi-cloud environments. Build agentic solutions using Vertex AI Agent Builder and ADK, connect agents securely to BigQuery/Spanner via MCP, implement streaming pipelines (Dataflow) for real-time inference, and manage model training, tuning, deployment, and evaluation on Vertex AI. Provide consultative guidance, cross-functional collaboration, and clear stakeholder communication to ensure business value from Generative AI solutions.

Lead design and delivery of an enterprise Generative AI platform across AWS Bedrock, Azure Foundry/OpenAI, and Databricks. Architect multi-cloud RAG/agent solutions, author IaC and Harness pipelines, enforce governance/FinOps/observability, mentor senior engineers, and enable data scientists and app teams to ship production GenAI at scale in regulated environments.

Senior technical leader responsible for architecting and operationalizing generative AI across the enterprise. Drive end-to-end GenAI architecture, select models and agent frameworks, productionize RAG and agent solutions, ensure observability, guardrails, and cost optimization, integrate with AWS and DevOps toolchains, advise CXO stakeholders, shape AI strategy, and define governance and upskilling programs.

Design, develop, and deploy generative AI models and AI-driven automation workflows. Integrate models via APIs, build inference pipelines, preprocess and manage training data, ensure data privacy, monitor and optimize model performance, collaborate with cross-functional teams, and document solutions.

Lead architecture and delivery of Generative AI solutions across Life & Annuities insurance, defining secure, scalable patterns (RAG, vectors, agents), integrating AI with policy administration, underwriting, and third-party systems, and enforcing governance, observability, and compliance while mentoring engineering teams and guiding cloud and data platform choices.

Evaluate, annotate, and quality-check AI-generated text, image, audio, and video content in Spanish. Identify edge cases, ensure guideline compliance, participate in calibration, and provide feedback to improve datasets and annotation workflows for generative AI models.

Design, build, and deploy LLM-based applications and multi-step AI workflows (retrieval, orchestration, agents) using large-scale structured and unstructured data. Partner with engineering to productionize solutions, implement evaluation and safety measures, ensure compliance and data governance, and communicate results to technical and non-technical stakeholders.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions on-site, collaborating with engineering teams to operationalize AI systems across multi-cloud platforms.

Own generative AI discovery, scaling, and maintenance for a portfolio of AI characters. Select and standardize models, build pipelines for face consistency and video, train and debug LoRAs, control GPU costs, design prompt architectures, define evaluation metrics and quality gates, and translate creative briefs into technical specs while testing frontier models and tooling to scale the studio.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

Lead generative AI image production for realistic personas and models. Build and optimize scalable generative pipelines, automate batch workflows, evaluate new models/tools, define technical direction and best practices, and improve image quality, consistency, speed, and cost-efficiency.

The role involves designing and deploying generative AI solutions, collaborating with teams, ensuring security and compliance, and guiding architectural decisions for AI initiatives.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Review, evaluate, and annotate AI-generated text, images, audio, and video in Simplified Chinese. Perform quality checks, identify edge cases, participate in calibration, and provide feedback to improve datasets and annotation guidelines.

Review, evaluate, and annotate AI-generated text, images, audio, and video; perform quality checks for accuracy and guideline compliance; identify edge cases and inconsistencies; contribute to dataset creation and calibration; provide feedback to improve annotation workflows and guidelines.

Lead research and development of generative AI and NLP models for large-scale email data. Innovate on fine-tuning (LoRA/adapters), quantization-aware training, and knowledge distillation to meet strict latency budgets. Build scalable training/evaluation pipelines, establish robust evaluation frameworks (LLM-as-a-judge, synthetic and human-in-loop), integrate AI-augmented developer tools, and set long-term technical direction while mentoring researchers and driving production-ready model deployments.

The Senior Software Engineer will design and implement Generative AI solutions, collaborate with teams, enhance AI applications, and mentor others in best practices.

Design and execute ML research and end-to-end model development for generative and summary-generation systems. Lead rigorous experiments, translate findings for stakeholders, partner with engineers to deploy models, track state-of-the-art advances, and define roadmaps to improve promotional writing and discovery for members.

Integrate LLMs, RAG, and agentic-AI into secure decision-support software. Design prompts and inference workflows, connect AI to backend services, evaluate outputs, build tests, document designs, and collaborate with engineering, security, and DevSecOps teams to deliver reliable mission-capable AI features.