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Network Ai Jobs (NOW HIRING)

Microsoft

Principal AI Network Architect

Redmond, WA · On-site

We are seeking a passionate Principal AI Network Architect to join the AI systems architecture team. The role includes network architecture evaluation, design and optimization for next-gen AI systems.

Avalore.ai

Network Engineer

Chantilly, VA · On-site

Job Summary : Avalore.ai is seeking an experienced Network Engineer who will be responsible for managing and maintaining the organization's complex and secure network infrastructure. The role ...

Jobgether

Our partner is looking for a Staff Network Engineer (AI Fabric, Datacenter and Edge Networking) based in Netherlands. This is a Staff-level networking role responsible for designing and operating ...

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How much do network ai jobs pay per year?

As of Sep 3, 2026, the average yearly pay for network ai in the United States is $106,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What is a Network AI?

A Network AI job involves developing and optimizing artificial intelligence models to manage, monitor, and enhance computer networks. Professionals in this role work on tasks like network automation, predictive analytics, and anomaly detection using machine learning. They collaborate with network engineers and data scientists to improve performance, security, and efficiency. This field requires expertise in AI, networking protocols, and data analysis tools.

What does a Network AI do?

Network AI professionals are commonly tasked with developing and deploying AI-driven solutions to monitor, secure, and optimize computer networks. This includes leveraging machine learning to detect anomalies or threats, automating network management tasks, and analyzing large datasets to improve network performance. They often work closely with network engineers, security teams, and data scientists to ensure that AI solutions are both effective and secure. The role offers continuous learning opportunities, as professionals must stay updated on the latest advancements in both networking and artificial intelligence.

What are the key skills and qualifications needed to thrive in the Network AI position?

To thrive as a Network AI professional, you typically need a solid background in computer networking, machine learning, and data analysis, often supported by a degree in computer science, information technology, or a related field. Familiarity with networking protocols (such as TCP/IP), AI frameworks (like TensorFlow or PyTorch), and relevant certifications (such as Cisco’s CCNA or CCNP) are highly valuable. Strong analytical thinking, collaboration, and effective problem-solving skills make candidates stand out in this role. These abilities are crucial for implementing intelligent network solutions, optimizing performance, and ensuring seamless integration of AI technologies in complex network environments.

What is the easiest Network Ai job to get into?

Entry-level Network AI roles typically include positions such as network technician or support specialist, which require basic understanding of networking concepts and some familiarity with AI tools. These jobs often require foundational certifications like CompTIA Network+ and minimal prior experience, making them accessible for newcomers to the field.

Which network AI job is high paying?

High-paying network AI jobs typically include roles such as AI Research Scientist, Machine Learning Engineer, and Data Scientist, especially those with expertise in deep learning, neural networks, and large-scale data processing. These positions often require advanced skills, certifications, and experience, and they tend to offer higher salaries due to the specialized knowledge involved.
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Network Ai jobs near you
Infographic showing various Network Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, and 6% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $106,570 per year, or $51.2 per hour.

Principal AI Network Hardware Systems Engineer

Microsoft

Redmond, WA • On-site

Full-time

Posted 28 days ago

Microsoft rating

8.5

Company rating: 8.5 out of 10

Based on 132 frontline employees who took The Breakroom Quiz

80th of 247 rated software companies

Job description

Overview
Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) powers the infrastructure behind Microsoft's Intelligent Cloud, delivering the foundational technologies that support services including Azure, Microsoft 365, Teams, Bing, Xbox Live, and more. As Microsoft continues to advance AI innovation, SCHIE is developing AI-native silicon and system-level solutions that enable next-generation AI training and inference at hyperscale.
The Platform Systems Engineering (PSE) team is seeking a Principal AI Network Hardware Systems Engineer to lead the architecture, bring-up, validation, optimization, and deployment of networking infrastructure for Microsoft's MAIA AI platform. This role combines networking hardware, systems architecture, AI infrastructure, and large-scale deployment to deliver industry-leading AI performance and reliability.
You will work across the networking stack, spanning high-speed SerDes, optics, cables, NICs, PHYs, switch silicon, AI communication frameworks, and distributed training systems. As a Principal engineer, you will influence architectural direction, guide technical strategy, and collaborate across silicon, firmware, hardware, software, validation, manufacturing, and Azure engineering teams.
This is a unique opportunity to shape the future of AI networking infrastructure and drive technologies that power Microsoft's next generation of hyperscale AI systems.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
AI Network Architecture & System Integration
  • Define and develop networking requirements for large-scale AI training and inference clusters.

  • Collaborate with silicon, system software, firmware, hardware, and Azure infrastructure teams to deliver scalable networking solutions from concept through datacenter deployment.

  • Participate in architecture reviews and influence next-generation AI networking roadmaps.

  • Define network concepts of operation, serviceability requirements, telemetry requirements, and operational models for AI infrastructure.

Layer 3 / Layer 4 Networking
  • Lead design and validation of IP-based AI networking solutions spanning TCP/IP, UDP, routing, congestion management, flow control, QoS, and traffic engineering.

  • Analyze transport-layer behavior and performance characteristics across large-scale distributed AI workloads.

  • Evaluate network protocol implementations and debug issues impacting latency, throughput, scalability, and reliability.

  • Drive optimization of network communication paths supporting distributed AI training and inference.

RDMA & AI Fabric Technologies
  • Design, validate, and optimize RDMA-based networking solutions for AI clusters.

  • Analyze RDMA performance, congestion behavior, packet loss, retransmissions, and collective communication efficiency.

  • Work closely with networking vendors and software teams to optimize AI fabric performance and workload scalability.

  • Develop validation methodologies for AI traffic patterns and collective communication workloads.

Performance Characterization & Validation
  • Develop and execute networking validation strategies covering functionality, performance, scale, interoperability, resiliency, and reliability.

  • Characterize network behavior under AI training and inference workloads.

  • Evaluate latency, bandwidth utilization, congestion events, flow distribution, and workload communication patterns.

  • Create and automate network stress, scale, and performance qualification methodologies.

Debugging & Root Cause Analysis
  • Lead end-to-end troubleshooting of networking issues across physical, data link, network, and transport layers.

  • Perform packet-level analysis and protocol debugging using telemetry, packet captures, performance counters, and diagnostic tools.

  • Investigate network switch, NIC, RDMA, routing, congestion control, and protocol-related issues.

  • Drive corrective actions and long-term reliability improvements using fleet telemetry and lab validation.

Automation & Observability
  • Build and improve network observability, diagnostics, telemetry, and monitoring solutions.

  • Develop tools and automation for network validation, performance analysis, and failure detection.

  • Improve engineering productivity through automated testing, qualification, and network health assessment frameworks.

Qualifications
Required Qualifications:
  • Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 7+ years technical engineering experience
    • OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience
    • OR equivalent experience
  • 8+ years of experience in NW HW development
  • 8+ years of experience in GPU based SU/SO development
  • 8+ years of hands on experience with HS interface architecture and development

Other Qualifications:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:
  • Experience with RDMA technologies, AI fabrics, and distributed training environments.
  • Understanding of RoCE, congestion control, ECN, PFC, DCQCN, and related AI networking technologies.
  • Experience with AI/ML workload communication patterns and collective operations.
  • Experience with SONiC, Linux networking, networking telemetry, and network operating systems.
  • Experience with network switches, SmartNICs, DPUs, NIC offloads, and large-scale cloud infrastructure.
  • Familiarity with AI networking technologies including Ultra Ethernet and hyperscale AI cluster architectures.
  • Experience developing network stress tools, validation frameworks, performance benchmarks, or observability solutions.
  • Knowledge of packet analysis tools, telemetry infrastructure, and network automation frameworks.
  • Exposure to high-speed networking environments (200G/400G/800G Ethernet).

#azure #MAIA #AI/ML #Networking Hardware
Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

Sourced by ZipRecruiter

Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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