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Contract Azure Infrastructure Engineer Jobs in Houston, TX

LLM Infrastructure Engineer

Houston, TX · On-site

$97K - $127K/yr

Deploy AI workloads in Azure environments (AKS, ACI, or Container Apps) Required Skills * Strong ... A hands-on engineer who understands how LLM systems run in production-from model loading and ...

Azure OpenAI / AI Cloud Engineer

Houston, TX · On-site

$50.25 - $67.25/hr

The ideal candidate will have a strong background in Azure infrastructure , MLOps , and enterprise ... Collaborate with data science and cloud engineering teams to operationalize AI models Required ...

Sr. Cloud Infrastructure Engineer

Houston, TX · On-site

$103K - $140K/yr

ECOM is looking for a Sr. Cloud Infrastructure Engineer to drive the technical vision of cloud ... or Azure environments. • Collaborate across teams to meet project goals. This will include ...

Developer & Infrastructure Expert Role Type: Contractor Location: Remote Job Overview We are ... Review workflows involving GitHub, GitLab, Azure DevOps, and JIRA . * Assess AI agents and ...

CW - Sr. Cloud Platform Engineer

Houston, TX · On-site

$53.25 - $71/hr

The Senior Cloud Platform Engineer is a hands-on technical role responsible for the administration ... Provision and modify Azure infrastructure using Terraform and Terraform Cloud, maintaining reusable ...

CW - Sr. Cloud Platform Engineer

Houston, TX · On-site

$53.25 - $71/hr

The Senior Cloud Platform Engineer is a hands-on technical role responsible for the administration ... Provision and modify Azure infrastructure using Terraform and Terraform Cloud, maintaining reusable ...

Sr. Cloud Infrastructure Engineer

Houston, TX · On-site

$103K - $140K/yr

The Sr. Cloud Infrastructure Engineer will work with IT management to drive the technical vision ... or Azure environments. • Collaborate across teams to meet project goals. This will include ...

Showing results 21-40

Contract Azure Infrastructure Engineer information

See Houston, TX salary details

$44.4K

$121.3K

$173.8K

How much do contract azure infrastructure engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for contract azure infrastructure engineer in Houston, TX is $121,345.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,700.00 and $134,700.00 per year, depending on experience, location, and employer.

What is the difference between Contract Azure Infrastructure Engineer vs Contract Cloud Network Engineer?

AspectContract Azure Infrastructure EngineerContract Cloud Network Engineer
CertificationsAzure Solutions Architect, Azure AdministratorCisco CCNA, CCNP, CCIE, Azure certifications
Work EnvironmentAzure cloud platforms, infrastructure deployment, and managementNetwork design, security, and connectivity in cloud environments
Employer & Industry UsageTech companies, cloud service providers, enterprises using AzureTelecom, data centers, cloud providers, enterprises with complex networks

The Contract Azure Infrastructure Engineer primarily focuses on deploying and managing Azure cloud infrastructure, while the Contract Cloud Network Engineer specializes in designing and securing network connectivity within cloud environments. Both roles require cloud and networking certifications and are in high demand across tech and enterprise sectors. The main difference lies in their focus areas: infrastructure deployment versus network security and connectivity.

What are the most commonly searched types of Azure Infrastructure Engineer jobs in Houston, TX?

The most popular types of Azure Infrastructure Engineer jobs in Houston, TX are:

What are popular job titles related to Contract Azure Infrastructure Engineer jobs in Houston, TX?

For Contract Azure Infrastructure Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Contract Azure Infrastructure Engineer jobs in Houston, TX look for?

The top searched job categories for Contract Azure Infrastructure Engineer jobs in Houston, TX are:

Infographic showing various Contract Azure Infrastructure Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $121,345 per year, or $58.3 per hour.

LLM Infrastructure Engineer

AMSYS Talent

Houston, TX • On-site

$97K - $127K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance APIs for model inference, optimizing GPU workloads, and deploying AI services in cloud environments.
This is an engineering-focused role, not research. We are looking for someone who has built and shipped AI systems into production and understands the challenges of scalable inference and model serving.
Key Responsibilities
  • Develop high-performance APIs using Python (3.10+) and FastAPI
  • Build and deploy LLM inference services using HuggingFace Transformers and PyTorch
  • Optimize GPU workloads and CUDA memory usage
  • Implement streaming inference APIs for real-time model responses
  • Containerize and deploy services using Docker and GPU-enabled infrastructure
  • Deploy AI workloads in Azure environments (AKS, ACI, or Container Apps)

Required Skills
  • Strong Python development experience (3.10+)
  • Hands-on experience building production APIs with FastAPI
  • Experience with HuggingFace Transformers and PyTorch
  • Solid understanding of REST API design
  • Experience deploying containerized applications with Docker

Nice to Have
  • Experience with OpenAI-compatible APIs, vLLM, or Text Generation Inference (TGI)
  • Experience deploying AI workloads on Azure GPU infrastructure
  • Familiarity with LoRA / PEFT fine-tuning
  • Exposure to legal or financial NLP use cases

Ideal Candidate: A hands-on engineer who understands how LLM systems run in production-from model loading and tokenization to GPU deployment and scalable APIs.