FriendliAI is the fastest inference cloud for agents, built to run frontier open-weight models in production at scale. Backed by Sierra Ventures.
About the role
FriendliAI is seeking a Forward Deployed Engineer to assist enterprises in deploying, scaling, and operating generative and agentic AI workloads on FriendliAI infrastructure. You will work directly with customers to solve and implement production-grade applications using our products, such as Serverless Endpoints, Dedicated Endpoints, or Container. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 3+ years of experience in cloud infrastructure, DevOps, or reliability engineering
- Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent
- Proficiency with Kubernetes, Docker, Terraform, and Helm
- Strong foundation in distributed systems, networking, and performance tuning
- Experience with GPU-based computing and generative AI model serving workloads
- Strong technical background in backend systems or AI tooling
More about this role
FriendliAI is seeking a Forward Deployed Engineer to assist enterprises in deploying, scaling, and operating generative and agentic AI workloads on FriendliAI infrastructure. You will work directly with customers to solve and implement production-grade applications using our products, such as Serverless Endpoints, Dedicated Endpoints, or Container.
Friendli Container is our service that allows customers to download our inference engine as Docker images and deploy it in their chosen environment, such as private clouds or on-premises. Our Friendli Container can be adopted directly to AWS EKS clusters using our EKS add-on product.
You will work directly on our customers’ projects, collaborating with their engineering teams to solve AI inference challenges like scaling, orchestration, and monitoring. This is a hands-on, customer-embedded role. If you have worked in DevOps, platform engineering, or SRE for AI applications, this is your ideal position.
Design and implement large-scale deployment architectures for LLM and multimodal inference
Deploy and manage containerized workloads across Kubernetes clusters
Diagnose production issues, such as performance bottlenecks, and implement...
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