Forward Deployed Engineer (AI Infrastructure)

Location: San Francisco, United States; on-site work at customer locations as required, with up to 25% travel

Company

hirify.global builds enterprise data platform software for capturing, cataloging, refining, enriching, and protecting massive datasets used in real-time analysis and AI training and inference.

What you will do

• Embed within strategic customer environments and own technical success from solution design through production operation.
• Collaborate with customer architects, operators, and developers to optimize infrastructure throughput and resolve complex issues.
• Develop custom API endpoints, automation tools, and scripts for critical customer workflows.
• Translate operational insights and customer requirements into precise technical improvements for core product teams.
• Test new builds, track hotfixes, review roadmap updates, and advocate for customer needs in product planning.

Requirements

• 5+ years of experience in a highly technical engineering role with customer-facing collaboration.
• Deep knowledge of distributed systems, high-performance file systems, storage protocols, and performance tuning.
• Strong understanding of InfiniBand, RoCE, and 100GbE+ high-throughput networking.
• Advanced Linux systems knowledge, including memory management and kernel mechanics.
• Proficiency in Python and C/C++, including debugging and contributing safely to complex enterprise codebases.
• Ability to travel or work on-site at customer locations as required, up to 25% travel.

Nice to have

• Experience operating large-scale AI training environments or HPC clusters.
• Experience with Docker, Kubernetes, PyTorch, or TensorFlow.

Culture & Benefits

• Work directly with strategic customers on large-scale infrastructure challenges.
• Collaborate globally with engineering teams on builds, hotfixes, and roadmap updates.
• Contribute directly to infrastructure supporting AI training, inference, and real-time data analysis.
• Operate at the cutting edge of AI infrastructure and the data stack.