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Ai Network Engineer Jobs (NOW HIRING)

Senior Network Engineer

San Francisco, CA ยท On-site

$190K - $280K/yr

About the Role Together AI is looking for a Senior Network Engineer to design, deploy, and operate the global network infrastructure supporting our production services and high-performance AI compute ...

We're looking for a highly experienced Network Engineer to join our growing team. The ideal ... Cloud & AI Infrastructure: Architect and operate Cisco Cloud & AI Infrastructure (CAI) solutions ...

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 ...

They are seeking a highly experienced Network Engineer to design, implement, and manage complex ... Architect and operate Cisco Cloud & AI Infrastructure (CAI) solutions, including data center fabric ...

The team seeks seasoned engineers to innovate and optimize cloud infrastructure. We are looking for a Principal AI Network Architect to join the team. Responsibilities * Technology Leadership ...

Reporting to the Senior Manager of Network Operations, the Network Engineer provides technical ... Demonstrated ability and willingness to use AI tools to improve productivity, decision-making, work ...

Network Engineer

El Segundo, CA ยท On-site

$115K - $165K/yr

Network Engineering: * Design, deploy, and maintain networking infrastructure * Configure and ... Use AI tools daily to accelerate compliance documentation, network analysis, vulnerability ...

Network Engineer

El Segundo, CA ยท On-site

$115K - $165K/yr

Network Engineering: * Design, deploy, and maintain networking infrastructure * Configure and ... Use AI tools daily to accelerate compliance documentation, network analysis, vulnerability ...

Network Engineering: * Design, deploy, and maintain networking infrastructure * Configure and ... Use AI tools daily to accelerate compliance documentation, network analysis, vulnerability ...

Meta's global network infrastructure underpins billions of user connections and powers some of the world's most demanding AI and distributed computing workloads. The Production Network Engineering ...

Network Engineering: * Design, deploy, and maintain networking infrastructure * Configure and ... Use AI tools daily to accelerate compliance documentation, network analysis, vulnerability ...

Network Engineer Reporting to: Director, Network Engineering Location: It is preferred that this ... The company combines market-leading AI precision care technology with extensive trusted patient ...

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Ai Network Engineer information

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$109K

$158K

How much do ai network engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for ai network engineer in the United States is $109,040.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,000.00 and $133,500.00 per year, depending on experience, location, and employer.

What is an AI network engineer?

AI Network Engineers are professionals who design, implement, and maintain network infrastructures optimized for artificial intelligence (AI) applications. They ensure that networks can handle the high data throughput and low latency requirements of AI workloads, such as machine learning model training and inference. Their responsibilities may include integrating AI-driven network management tools, optimizing data flow for distributed AI systems, and ensuring data security and reliability. AI Network Engineers often collaborate with data scientists, AI researchers, and IT teams to deploy scalable and efficient AI solutions. As AI adoption grows, their role becomes increasingly important in supporting advanced technologies across industries.

What are the key skills and qualifications needed to thrive as an AI network engineer?

To thrive as an AI Network Engineer, you need expertise in computer networking, AI/ML concepts, and a strong background in computer science or a related field, often supported by a relevant degree or certifications like CCNP or AWS Certified Solutions Architect. Familiarity with network simulation tools, AI frameworks (such as TensorFlow or PyTorch), and network automation platforms is typically required. Problem-solving, analytical thinking, and effective communication are essential soft skills in this role. These skills are crucial for designing, deploying, and optimizing intelligent network systems that support scalable and efficient AI-driven solutions.

What are some common challenges AI network engineers face when deploying AI models at scale within enterprise networks?

AI Network Engineers often encounter challenges related to ensuring low-latency data transfer, handling large volumes of real-time data, and maintaining high security standards during AI model deployment. Integrating AI workloads with existing network infrastructure can require careful optimization of bandwidth and compute resources to prevent bottlenecks. Additionally, collaborating with data scientists and IT teams is essential for troubleshooting and refining deployment processes while keeping the network stable and scalable.
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Infographic showing various Ai Network Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, and 6% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $109,040 per year, or $52.4 per hour.

Senior Network Engineer

San Francisco, CA โ€ข On-site

Together AI
Internet and ITย โ€ขย 51 - 200 employees

$190K - $280K/yr

Full-time

Medical

Re-posted 28 days ago


Job description

About the Role

Together AI is looking for a Senior Network Engineer to design, deploy, and operate the global network infrastructure supporting our production services and high-performance AI compute environments.

This is a hands-on engineering role for someone with deep networking expertise who can also troubleshoot across Linux, Kubernetes, automation, and application boundaries. You will work on large-scale, multi-vendor data center networks and help ensure they remain highly available, reliable, scalable, and performant.

The ideal candidate has strong networking fundamentals, experience operating complex networks at scale, and a structured, evidence-based approach to troubleshooting. You should be comfortable owning problems from initial investigation through root cause and resolution, including situations where the issue may extend beyond the network itself.

Requirements

  • 8+ years of professional experience designing, building, and supporting large-scale production data center, cloud, service-provider, or high-performance computing networks (excluding enterprise networks).
  • Deep understanding of TCP/IP and strong experience with technologies such as BGP, OSPF, VXLAN, EVPN, ECMP, and QoS.
  • Experience designing and supporting multi-tenant network environments using technologies such as VRFs, VLANs, overlays, and policy-based segmentation.
  • Hands-on experience deploying and troubleshooting network platforms from vendors such as Arista, Cisco, Juniper, and NVIDIA.
  • Strong troubleshooting skills using tools such as Wireshark, tcpdump, MTR, curl, nmap, and standard Linux networking utilities.
  • Ability to diagnose connectivity, latency, packet-loss, routing, and performance issues across the network, host, and application layers.
  • Experience developing or maintaining network automation using Python, Ansible, or similar tools.
  • Experience working through a Git-based software development lifecycle, including branching, code review, validation, linting, testing, CI/CD, deployment, and rollback.
  • Working knowledge of Kubernetes networking, including pods, services, CNIs, and basic connectivity troubleshooting.
  • Foundational knowledge of RDMA networking and technologies such as RoCE or InfiniBand.
  • Experience with cloud networking in AWS, GCP, or Azure.
  • Strong Linux administration and troubleshooting skills.

Responsibilities

  • Design, deploy, operate, and maintain global, multi-vendor, multi-protocol networks supporting high-performance AI compute infrastructure.
  • Troubleshoot complex network and application-connectivity issues, identify root causes, and drive problems through resolution.
  • Analyze telemetry, packet captures, logs, and performance data to identify network degradation, congestion, packet loss, and capacity constraints.
  • Participate in architecture and design reviews to ensure solutions meet requirements for performance, availability, scalability, security, and operational supportability.
  • Develop and maintain automation, validation, and operational tooling that improves network reliability and reduces manual effort.
  • Evaluate network hardware, software, optics, and emerging technologies for use in production environments.
  • Establish standards and operational best practices for network design, deployment, monitoring, change management, and incident response.
  • Lead projects addressing complex technical challenges and contribute directly to the network engineering roadmap.
  • Partner with infrastructure, systems, security, and application teams to troubleshoot issues that cross traditional ownership boundaries.

Preferred

  • Hands-on experience deploying or operating RoCE and/or InfiniBand fabrics.
  • Experience supporting GPU clusters, HPC environments, distributed storage, or other high-bandwidth and latency-sensitive workloads.
  • Understanding of AI training and inference traffic patterns and the demands they place on network infrastructure.
  • Experience operating networks spanning thousands of devices, multiple data centers, and multiple geographic regions.
  • Familiarity with AI-assisted engineering tools and the ability to validate, test, and safely deploy AI-generated automation or code.
About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacyย ย