Network Infrastructure Engineer - AI Data Platform
Location: Hybrid - Ashburn
Compensation: $125K - $150K
Join a lean, technical team building the critical infrastructure that delivers massive amounts of web data to companies training the world’s most powerful AI models. The client operates a vast distributed crawler, granting unique access to high-quality public web data at a global scale. Their work involves building advanced pipelines for ingesting, segmenting, and annotating billions of videos, transcripts, and audio files, directly powering dataset creation for frontier AI labs.
The client is looking for a talented Network Infrastructure Engineer with significant experience in infrastructure and network architecture design. You will be responsible for building and maintaining the robust physical and cloud infrastructure that powers their AI-driven platform. Your work will directly impact the efficiency, security, and performance of our systems at massive scale.
This role requires deep expertise across network architecture, physical deployment, cloud services, and automation (Infrastructure as Code).
- Infrastructure Design and Implementation: Oversee the design, configuration, and deployment of networks, servers, network switches, firewalls, and applications. This includes deploying physical infrastructure at our data center.
- System Configuration & Virtualization: Oversee the configuration of servers with virtualization and troubleshoot complex application issues across the stack.
- Scalability & Security: Ensure all infrastructure solutions meet stringent business needs for high scalability and industry-leading security standards.
- Network Management: Ensure correct configuration of all network components, including routers, switches, firewalls, and VPNs.
- Maintenance and Support: Ensure regular maintenance of servers, networks, and other infrastructure components to guarantee maximum uptime and reliability.
- Performance Monitoring: Monitor system performance and proactively implement solutions to enhance reliability, security, and scalability.
- DevOps Integration: Collaborate closely with engineering teams to integrate DevOps best practices into the development and deployment lifecycle, promoting automation.
