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Remote Ai Infrastructure Engineer Jobs in Seattle, WA

Lightning AI

Infrastructure Engineer (Storage)

Seattle, WA · On-site +1

$122.40K - $160.60K/yr

Remote; San Francisco, California, United States; Seattle, Washington, United States Who We Are ... What We're Looking For Lightning AI is seeking a Storage Infrastructure Engineer to join our ...

The AES Group

Infrastructure Engineer

Seattle, WA · Remote

$110K - $144.30K/yr

Role - Infrastructure Engineer Location - Remote, USA Let's create our future together at The AES ... AI, and other emerging technologies. Why Join The AES Group, Inc. * Competitive compensation ...

Lightning AI

Infrastructure Operations Engineer

Seattle, WA · On-site +1

$160K - $200K/yr

Infrastructure Operations Engineer Lightning AI is the company behind PyTorch Lightning. Founded in ... This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote ...

Alignerr

C# Infrastructure Engineer - Data Pipelines

Seattle, WA · Remote

$122.40K - $160.60K/yr

C# Infrastructure Engineer - Data Pipelines (AI Training) About the Role What if your C# skills ... This is a fully remote, flexible contract role working alongside leading AI labs on real production ...

Omnidian

Senior Infrastructure Engineer

Seattle, WA · Remote

$111.10K - $151K/yr

The Job As a Sr. Infrastructure Engineer at Omnidian, you will drive core infrastructure execution ... AI-Augmented Engineering: Proactively leverage generative AI tools to validate administrative ...

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Remote Ai Infrastructure Engineer information

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$52.9K

$144.6K

$207.1K

How much do remote ai infrastructure engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for remote ai infrastructure engineer in Seattle, WA is $144,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,300.00 and $160,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote AI Infrastructure Engineer, and why are they important?

To thrive as a Remote AI Infrastructure Engineer, you need expertise in cloud computing, distributed systems, and software engineering, often supported by a degree in computer science or a related field. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud platforms such as AWS, Azure, or GCP is typically required, along with knowledge of CI/CD pipelines and AI/ML frameworks. Strong problem-solving skills, self-motivation, and effective remote communication are essential soft skills for success in this role. These skills ensure robust, scalable AI infrastructure that supports rapid innovation and seamless collaboration across distributed teams.

What are some common challenges faced by Remote AI Infrastructure Engineers, and how can they be addressed?

Remote AI Infrastructure Engineers often encounter challenges such as managing distributed systems, ensuring robust data pipelines, and maintaining high system reliability across different time zones. Collaboration with cross-functional teams can require clear communication and effective use of remote tools. To address these challenges, it's important to establish strong documentation practices, schedule regular check-ins, and utilize automated monitoring and deployment solutions. Staying proactive and adaptable helps ensure seamless infrastructure performance and team alignment.

What is a Remote AI Infrastructure Engineer?

A Remote AI Infrastructure Engineer is a professional who designs, builds, and maintains the systems and tools necessary to support artificial intelligence (AI) projects, all while working remotely. Their responsibilities often include developing and optimizing cloud or on-premise infrastructure, ensuring scalability, managing data pipelines, and supporting machine learning workflows. They work closely with data scientists and software engineers to ensure AI models can be efficiently trained, deployed, and monitored in production environments. The remote aspect allows them to perform these tasks from anywhere, using collaboration tools and cloud platforms.
What are the most commonly searched types of Ai Infrastructure Engineer jobs in Seattle, WA? The most popular types of Ai Infrastructure Engineer jobs in Seattle, WA are:
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What cities near Seattle, WA are hiring for Remote Ai Infrastructure Engineer jobs? Cities near Seattle, WA with the most Remote Ai Infrastructure Engineer job openings:
Remote Ai Infrastructure Engineer jobs near you
Infographic showing various Remote Ai Infrastructure Engineer job openings in Seattle, WA as of May 2026, with employment types broken down into 90% Full Time, 4% Part Time, and 6% Contract. Highlights an 62% Physical, 5% Hybrid, and 33% Remote job distribution, with an average salary of $144,605 per year, or $69.5 per hour.

AI Infrastructure Engineer

Bright Vision Technologies

Bellevue, WA • Remote

$121.30K - $159.10K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled AI Infrastructure Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. AI Infrastructure Engineer Job Title: AI Infrastructure Engineer
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Experience: 6+ years
Salary - 100 K - 150 K
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are seeking an AI Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control. The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work.
Key Responsibilities
  • Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations.
  • Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams.
  • Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering.
  • Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate.
  • Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication.
  • Build observability for AI workloads including utilization, throughput, training stability, and failure-mode analytics.
  • Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scale.
  • Drive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizing.
  • Develop developer tooling and paved-road workflows that let researchers launch experiments safely and efficiently.
  • Partner with research and applied ML teams to plan capacity for upcoming training runs.
  • Implement security controls, isolation, and access management for multi-tenant AI infrastructure.
  • Drive automation across cluster provisioning, lifecycle management, and configuration enforcement.
  • Maintain runbooks, capacity dashboards, and operational documentation for the AI platform.
  • Stay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • Six or more years of experience in infrastructure, platform, or HPC engineering.
  • Hands-on experience operating GPU clusters or large-scale ML training infrastructure.
  • Strong proficiency in Python and at least one systems language such as Go or C++.
  • Deep understanding of distributed training, accelerator architectures, and collective communication.
  • Experience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloads.
  • Strong understanding of Linux internals, networking, and high-performance storage.
  • Experience with at least one major cloud provider’s ML infrastructure offerings.
  • Strong software engineering practices including testing, CI/CD, and code review.
  • Excellent communication and cross-functional collaboration skills.
Preferred Qualifications
  • Experience operating InfiniBand or RDMA networking at scale.
  • Contributions to open-source ML infrastructure projects.
  • Familiarity with custom orchestrators or research-grade training stacks.
  • Exposure to frontier model training operations.
  • Experience with FinOps for AI workloads.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to jenny@bvteck.com or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”
 

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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