Forward Deployed Engineer (AI)

Location: San Mateo, United States; work arrangement: on-site

Company

hirify.global provides model APIs, dedicated inference infrastructure, and agent sandbox environments for building, deploying, and scaling production AI applications.

What you will do

• Own the technical relationship with customers from evaluation through production.
• Understand customer architectures, workloads, and engineering requirements.
• Deploy and integrate model APIs, inference endpoints, dedicated model serving, and agent sandbox environments.
• Debug complex issues across APIs, containers, Linux, networking, model serving, and distributed systems.
• Analyze inference performance, including latency, throughput, concurrency, caching, and reliability.
• Build customer integrations, prototypes, automation, and reusable tooling while translating recurring problems into product requirements.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field.
• Strong software engineering fundamentals and proficiency in Python plus at least one additional programming language.
• Strong understanding of APIs, Linux, networking, and cloud-native applications.
• Experience debugging complex technical systems and communicating effectively with customers and engineering teams.
• High ownership and the ability to operate across engineering, product, and customer problems in ambiguous environments.

Nice to have

• Experience with LLMs, AI agents, inference infrastructure, or model-serving performance.
• Familiarity with vLLM, SGLang, Ray, Docker, Kubernetes, or distributed serving frameworks.
• Experience building coding agents, AI agents, or sandboxed execution systems.
• Background in solutions engineering, developer relations, technical consulting, or other customer-facing technical roles.
• Professional working proficiency in Mandarin Chinese, open-source contributions, startup experience, or significant technical side projects.

Culture & Benefits

• Work directly with customers building demanding AI applications.
• Collaborate with engineering teams across the United States and Asia.
• Combine software engineering, infrastructure, product, and customer success work.
• Influence the product roadmap through exposure to real production workloads.