Top AI Jobs in Austin, TX

Lead and build Deepgram's AI enablement function: prototype and ship reusable agents, MCP servers, paved-road workflows, prompt and retrieval patterns, and an enablement hub. Drive company-wide AI adoption with measurable productivity metrics, embed safe-use guardrails, partner across Platform, Security, Data, and People Ops, and grow a central team and distributed champions network.

Lead design, build, and operate scalable observability systems for distributed cloud and on-vehicle environments. Contribute code and reviews, create technical designs, build tooling to collect observability signals, run PoCs for new tools, partner with engineering teams, define SLIs/SLOs, guide roadmap decisions, and mentor engineers to improve developer productivity and reliability.

Lead and hands-on build the AI Gateway: set technical/product direction, implement core systems and developer tooling, recruit and mentor engineers, collaborate with platform teams, and ship high-velocity AI infrastructure and agent tooling.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

Lead end-to-end delivery of ML infrastructure and AI tooling programs, defining architecture and rollout strategies for training, serving, and monitoring. Coordinate research, engineering, product, and data teams to optimize inference cost/latency, build internal tools for experiment tracking and model versioning, and resolve bottlenecks to enable faster, scalable ML deployments.

Lead product vision, strategy, and execution for Realtor.com's Enterprise AI portfolio across LLM platform, developer tooling, agentic solutions, and enablement. Drive prioritization, VOC discovery, OKR-based measurement, vendor relationships, cross-functional delivery, and executive storytelling. Mentor PMs, grow the AI community, and ensure scalable, governed AI adoption across engineering and business users to deliver measurable business impact.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The role involves architecting AI applications, delivering scalable solutions, conducting research, and implementing high-quality code for cloud platforms. Requires collaboration and effective communication.

Lead design and implementation of agentic AI workflows and integrations for Acquia DAM. Build, ship, and observe production AI features (auto-tagging, search, governance), set AI engineering standards, evaluate models and tooling, mentor engineers, and represent AI architecture to product and customers.

Evaluate and validate AI Coach chat outputs for accuracy and risk, act as subject-matter expert in personal financial planning, identify enhancements, escalate issues to Ops/Product/Compliance, and contribute reusable solution libraries to improve member experience.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.

Take Deepgram's speech models and optimize, compile, and run them on resource-constrained embedded and edge hardware. Work across model compression, runtime performance (C/C++/Rust), RTOS/bare-metal and embedded Linux environments, vendor NPUs/DSPs and inference runtimes, benchmarking, deployment pipelines, OTA updates, and partner with silicon vendors to enable real-time, low-power on-device voice experiences.

Design, build, deploy, and iterate production-ready AI agents and LLM-based solutions that integrate with enterprise workflows. Rapidly prototype, evaluate, and optimize agents for performance, cost, and adoption. Partner across functions to redesign workflows, contribute to an AI Center of Excellence, and ensure responsible, secure, and scalable agent development.

Design, build, and operate large-scale LLM infrastructure and data platforms for training, fine-tuning, and inference. Provision GPU clusters, optimize GPU utilization, implement model lifecycle management, deploy inference frameworks, create evaluation and observability systems, and collaborate with data scientists to productionize AI capabilities. Mentor engineers and enforce MLOps/DataOps best practices.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.

The Staff AI Performance Engineer will optimize performance across ARM-based architectures and distributed systems, analyzing AI workloads and collaborating to enhance system efficiency.

As a Sr. AI Platform Engineer, you'll manage and improve AI tool operations, ensure security and governance, and support users across the company.

Design, build, and deploy AI agents and multi-step automation workflows for Client Experience. Integrate systems via APIs, partner with stakeholders, ensure governance and security, and track metrics for efficiency and customer outcome improvements.

Lead product for AI Corps: define roadmap, metrics, and platform powering fellow recruitment, matching, deployment, and enterprise L&D. Partner with Earned Revenue, Curriculum, Engineering, and Anthropic to run discovery, experiments, and ship high-quality experiences that scale to enterprise customers.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

Develop AI solutions for marketing teams, integrating AI agents and workflows while coaching teams for self-sufficiency in AI use.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

The role involves developing, testing, and validating Generative AI agents and maintaining automated testing standards. Responsibilities include mentoring junior associates, analyzing complex issues, and applying governance controls in AI-driven solutions.

As an AI Engineering Manager at PwC, you will lead the design and operation of AI-powered platforms, mentor engineers, and ensure project delivery excellence while focusing on security and scalability.