Built In Austin’s September 29, 2026 roundup names 14 employers it describes as active in the metro area and regular recruiters of AI talent: 2K, General Motors, Google, Dell Technologies, Apple, Expedia Group, Oracle, Visa, IBM, Motive, Amazon, Tesla, NVIDIA and Optum. The list spans gaming, vehicles, cloud infrastructure, enterprise software, payments, healthcare and more—but it is an employer guide, not confirmation that each company has an AI engineer opening today.
Which Austin employers are included?
The following companies and work areas are summarized from Built In Austin’s employer roundup. Treat it as a map of the local AI engineering landscape rather than an independently audited ranking or a live requisition list.
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| Employer | Work described in Austin | Technical layer or domain |
|---|---|---|
| 2K | AI for computer-controlled players and internal workflows | Gaming and applied AI |
| General Motors | Driver-assistance systems and OnStar connected-vehicle cloud software at its Austin Innovation Center | Automotive, autonomy and cloud |
| Machine-learning operations, TPU compiler pipelines, Google Cloud infrastructure and Android AI features | Compute, cloud and product AI | |
| Dell Technologies | AI infrastructure involving servers, GPUs and storage at its Round Rock headquarters | Hardware and enterprise infrastructure |
| Apple | Machine-learning verification, inference systems and Neural Engine software at a North Austin campus | Consumer devices and on-device AI |
| Expedia Group | AI- and ML-enabled features for its offerings | Travel technology and applied AI |
| Oracle | AI agents and database technologies for running large language models against enterprise data at its Austin headquarters | Enterprise software and cloud |
| Visa | Payment security, deep-learning models and predictive fraud scoring | Payments and financial technology |
| IBM | Foundation-model work, including Granite, and infrastructure for watsonx.ai | Enterprise AI and platforms |
| Motive | IoT hardware and AI for fleet tracking, driver safety, compliance and maintenance | Transportation and applied systems |
| Amazon | Annapurna Labs custom AI chips and machine-learning infrastructure for AWS and generative-AI products | Chips, cloud and infrastructure |
| Tesla | Neural networks for driving systems and the Cortex compute cluster for Full Self-Driving, Cybercab and Optimus | Automotive AI and compute |
| NVIDIA | CUDA libraries, TensorRT inference tools and networking software | Semiconductors and AI developer infrastructure |
| Optum | AI specialist roles across locations, including remote roles in Texas | Healthcare and applied AI |
What kinds of AI engineering jobs appear in Austin?
A snapshot of the Built In Austin AI Engineer job board showed examples across applied AI, platform engineering, enterprise automation, AI safety and production machine learning. The sample included roles attributed to General Motors, Realtor.com, PwC, Toast and NVIDIA, among others. This is a changing board, so a listing’s presence in a snapshot does not establish that it remains open.
The spread matters when comparing employers: an AI engineer role can focus on model or research work, infrastructure and deployment, applied product engineering, or automation. A company’s industry alone does not tell you which layer a particular job covers; read the responsibilities in the live posting.
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Which skills should applicants look for?
Sampled postings named Python, large language models (LLMs), retrieval-augmented generation (RAG), evaluation, observability, cloud platforms and agent systems. These are examples seen across individual listings, not a universal checklist for Austin AI engineer jobs. Match your preparation to the role’s stated responsibilities and seniority.
What do Austin AI engineer jobs pay?
Two listing-specific advertised ranges in the sampled job-board snapshot were $163,000–$250,000 for a General Motors Lead AI Software Engineer role and $151,000–$187,000 for a PwC CTIO-AI Engineer-Sr Associate role. They describe those postings only; they do not establish typical pay for AI engineers in Austin, and listings can change.
Built In’s roundup also cites an Austin average of about $145,000 and attributes it to Levels.fyi, but the article does not state the estimate’s observation date or methodology. It should not be treated as a verified current average.
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Compare the actual openings along four dimensions rather than choosing by company name alone:
- Technical layer: chips and compute, cloud or platform engineering, or application-level AI.
- Domain: automotive, enterprise, finance, healthcare, travel, gaming or fleet operations.
- Role type: research and model work, infrastructure, applied product engineering or automation.
- Posting details: seniority, location, work arrangement and the specific qualifications listed.
The roundup does not provide a consistent employer-by-employer dataset for pay or benefits, so those are best compared from current individual postings.
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How to verify an opening before applying
- Use the employer name and role description in the roundup to identify relevant teams and terminology.
- Search the company’s own careers site for “AI engineer” and related titles such as machine-learning engineer, applied scientist or AI software engineer.
- Confirm that the requisition is still open and that its location, remote or hybrid arrangement, seniority and qualifications fit your situation.
- Use any job-board listing as a lead, then rely on the employer’s live posting for application instructions and current terms.
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