Lead AI Infrastructure Engineer Austin TX Remote

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Lead AI Infrastructure Engineer Austin TX / Silicon Hills ( Remote/Hybrid) -$210k -$275k: The definitive 2026 Guide

The AI Revolution in “Silicon Hills” of Austin Texas, is the New Global compute capital

Lead AI Infrastructure Engineer Austin TX As we cross into 2026, the “Silicon Hills” of Austin Texas, have evolved from secondary tech Hub into the primary engine of global AI Infrastructure, while the early 2020’s were defined by software and ‘Big Data” the current era is defined by sheer scale of AI compute Lead AI Infrastructure Engineer Austin TX

Lead AI Infrastructure Engineer Austin TX At diceusajobportal, we have seen a massive 40% increase in requirements for engineers who don’t just understand code, but understand the metal the GPU’s, the InfiniBand networks, and the cooling systems that allows LLms to exit, The spific requirement for a Lead AI Infrastructure Engineer represents the top 1% of Opportunities in the Austin market today

Lead AI Infrastructure Engineer Austin TX Remote
Lead AI Infrastructure Engineer Austin TX Remote

Role Overview: Architecting the future of Generative Intelligence 

This is not a standard DevOps role, As a Lead AI Infrastructure Engineer, you will be responsible for the Foundation Layer of a generative AI platform serving millions of token per second Lead AI Infrastructure Engineer Austin TX

Location: Austin, TX ( Silicon Hills, Domain Area ) Lead AI Infrastructure Engineer Austin TX

Model: Hybrid ( 3days on-site to manage the GPU Clusters )

Total Compensation: $210,000 – $275,000 + Equity + Performance Bonuses.

C2C Rates: Top-tier rates reaching $185/hr for elite contractors

Deep -Drive: The Technical pillars of 2026 AI Infrastructure 

To hit the $275k salary bracket, candidates must be a masters of three specific technical domains that have become the standards in 2026

1, GPU Cluster Orchestration & Scheduling

The heart of this role in the management of NVIDIA H100and H200 Tensor core cluster In 2026, the challenges isn’t just having GPU’s its ensuring they are never idle

Technical Focus: You will Impalement advanced scheduling using Kubernetes (k8s) with customized karpenter providers

The Goal: Maximizing Floating point Operations ( FLOPs) While minimizing thermal throttling across thousands of nodes

Reference: we recommend reviewing the NVIDIA AI Enterprise documentation for current cluster management standards

Lead AI Infrastructure Engineer Austin TX Vector Data Architecture at Billion Object scale

Retrieval -Augmented Generation is the dominant architecture of 2026, This role requires an engineer who can move beyond basic setups and scale vector Databases like pin core, Milvus or Waite to handle billions of high dimensional embeddings

Technical Focus: You will lead the transition from single -node instance to distributed, sharded vector cluster that provide sub-50ms and drift detections

3, LLMOps & the Golden Pipelines

Standard CI-CD doesn’t work for AI, you will be building an LLMOps pipelines that includes automated model evaluation weight versioning, and drift detection

Technical focus: Implementing vLLM and Tensors-LLM for Inference Optimization, ensuring that company’s Time to first Token

Lead AI Infrastructure Engineer Austin TX Strategic Challenges: What you’ll solve in your First 90days 

A; The GPU cost Bottleneck

In Austin’s competitive landscape, compute costs are #1 threat to AI startups, you will Implement ” spot Instance” strategies and preemptible GPU Orchestration to cut training costs by 30% without losing progress, using tools like PyTorch FSDP

B; The Data Gravity problem

Moving petabytes of training data into GPU Cluster is slow and expensive, you will architect a distributed file system ( using Luster or Weka) that ensure the GPU’s are always “fed” with data at line rate speeds

C, Post-training Reliability 

Quantization is the key to 2026, you will lead to effort to quantize 70B+parameter models down to 4-bit or 8-bit precision, allowing them to run on cheaper, more available hardware without losing accuracy

Career Growth & Market Comparison 

Why choose Austin Over Bellevue or NYC ? While NYC own Fintech, Austin owns the compute, by taking this role, you are position yourself at the center of the hardware software convergence

Compare the markets in our Austin vs Bellevue 2026 Hub Report

Master the coding requirements in our Top 20 Python for AI Guide 

How to Apply: Join the Silicon Hills Elite 

DiceUSAJobPortal is more than a job board; we are your career partner. To apply for this Lead AI Infrastructure position, please ensure your resume highlights your direct experience with NVIDIA cluster management and distributed inference Lead AI Infrastructure Engineer Austin TX

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