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Remote Ai Infrastructure Engineer Jobs in Reston, VA

Eliassen Group

Infrastructure Engineer

Washington, DC · Remote

$60 - $70/hr

Hybrid 3 days onsite / 2 days remote in Washington, DC Our client seeks a Senior Infrastructure ... All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring ...

Wells Fargo

Lead Infrastructure Engineer

Mclean, VA · On-site +1

$108K - $142K/yr

... remote state securely, and automating AWS infrastructure deployments at scale. Desired ... Hands-on experience with Site Reliability Engineering (SRE) or Cloud Operation principles ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

System One

AWS Cloud Infrastructure Engineer

Mclean, VA · Remote

$110K - $144K/yr

Cloud Infrastructure & Automation Engineer -- AWS / Terraform Remote Public Trust eligibility ... Experience using AI-assisted coding tools such as GitHub Copilot, ChatGPT, Cursor, or similar tools ...

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Remote Ai Infrastructure Engineer information

See Reston, VA salary details

$48.4K

$132.2K

$189.3K

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

As of Jul 25, 2026, the average yearly pay for remote ai infrastructure engineer in Reston, VA is $132,194.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $146,700.00 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 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 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 are popular job titles related to Remote Ai Infrastructure Engineer jobs in Reston, VA? For Remote Ai Infrastructure Engineer jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Remote Ai Infrastructure Engineer jobs in Reston, VA look for? The top searched job categories for Remote Ai Infrastructure Engineer jobs in Reston, VA are:
What cities near Reston, VA are hiring for Remote Ai Infrastructure Engineer jobs? Cities near Reston, VA 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 Reston, VA as of July 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 100% Remote job distribution, with an average salary of $132,194 per year, or $63.6 per hour.

AI Infrastructure Engineer

Bright Vision Technologies

Herndon, VA • Remote

$100K - $150K/yr

Full-time

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

Job description

AI Infrastructure Engineer- Remote
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. 
 
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. 
Job Title: AI Infrastructure Engineer
Location: 100% Remote (United States)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. 
Job Summary
We are seeking an AI Performance Optimization Engineer to focus on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans the full stack from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization. The ideal candidate has demonstrated an impact on production of AI workloads, with strong instrumentation and measurement discipline that enables rigorous, data-driven optimization decisions. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.
Key Responsibilities
  • Profile and optimize end-to-end AI training and inference pipelines for throughput, latency, and cost.
  • Identify and eliminate bottlenecks across data loading, model compute, communication, and memory.
  • Implement and tune quantization, sparsity, and pruning strategies to reduce model footprint and accelerate inference.
  • Optimize distributed training using tensor parallelism, pipeline parallelism, FSDP, and ZeRO-style sharding.
  • Tune attention implementations using Flash Attention, paged attention, and related techniques.
  • Implement KV cache optimization, continuous batching, and speculative decoding for LLM serving.
  • Drive compiler-level optimizations using Triton, XLA, Torch Inductor, or TVM, working with the broader ML framework community to land improvements that translate into measurable end-to-end performance gains.
  • Optimize data pipelines, sharding strategies, and storage access patterns for high-throughput training.
  • Build and maintain rigorous benchmark suites and regression frameworks across workloads.
  • Collaborate with ML and platform engineering teams to embed best practices in standard pipelines.
  • Drive cost-efficiency improvements through model architecture, hardware selection, and scheduling strategies.
  • Evaluate new hardware and software offerings and advise on adoption.
  • Document performance tuning playbooks and share findings broadly across engineering teams.
  • Stay current with AI systems to research and translate advances into production improvements.
Required Qualifications
  • Bachelor\'s or master\'s degree in computer science, Computer Engineering, or related field.
  • Six or more years of experience in performance engineering, ML systems, or HPC.
  • Strong proficiency in Python and C++.
  • Hands-on experience optimizing deep learning workloads on modern GPUs.
  • Deep understanding of distributed training and inference techniques.
  • Experience with profiling tools across CPU, GPU, and distributed systems.
  • Familiarity with model compression techniques and their accuracy implications.
  • Strong grasp of memory hierarchies, communication primitives, and parallelism strategies.
  • Excellent measurement, debugging, and analytical reasoning skills.
  • Strong communication and collaboration skills.
Preferred Qualifications
  • Experience optimizing LLM inference at production scale.
  • Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
  • Familiarity with custom kernel authoring in Triton or CUTLASS.
  • Experience with FinOps for AI workloads.
  • Publications or talks on AI systems performance.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to boon@bvteck.com or contact us at (908) 650-6699. Learn more about Bright Vision Technologies at www.bvteck.com. 
 
Bright Vision Technologies is an Equal Opportunity Employer. 
 

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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