Forward Deployed Engineer

FriendliAI Corp.
United States
24 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Cloud Computing Computer Engineering Continuous Integration Software Debugging DevOps Distributed Systems Network Security Performance Tuning Reliability Engineering Prometheus
+17 more
Graphics Processing Unit (GPU) DeepSpeed Large Language Models Grafana Kubernetes Helm Charts Backend Containerization Kubernetes Information Technology Machine Learning Operations TensorRT VLLM Model Inference Terraform Oracle Cloud Infrastructure Serverless Computing Docker

Job description

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 temporary fixes as needed
  • Collaborate with customers’ DevOps teams to integrate FriendliAI’s infrastructure into their CI/CD workflows
  • Develop scripts, Helm charts, and Terraform modules that simplify repeated deployments
  • Contribute field insights to shape our platform reliability, observability, and scaling strategies
  • Lead workshops, technical sessions, or webinars to help customers master infrastructure best practices.

Requirements

  • 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
  • Experience operating workloads on AWS, GCP, or OCI
  • Excellent problem-solving and debugging skills in real-world environments

Preferred Experience

  • Experience deploying large models (LLMs, diffusion models) on GPUs or clusters
  • Familiarity with inference frameworks (Triton, vLLM, TensorRT, DeepSpeed-Inference)
  • Familiarity with observability stacks (Prometheus, Grafana, Loki, ELK, OTEL)
  • Understanding of networking security and compliance frameworks (e.g., SOC 2)
  • Experience supporting on-prem or hybrid-cloud deployments

Benefits & conditions

  • A front-row seat to the generative AI infrastructure revolution
  • Competitive compensation and benefits package
  • Daily lunch and dinner provided; unlimited snacks and beverages
  • Health check-up and top-tier hardware support
  • Flexible working hours and a highly collaborative environment

About the company

FriendliAI is the fastest inference cloud for agents, built to run frontier open-weight models in production at scale. It delivers up to 7x faster output token speed, up to 90% lower inference costs, and 99.99% uptime across the most demanding agent workloads - long-context inference, real-time streaming, and accurate tool calling.

We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference stack, we are building the platform teams can actually rely on. FULL_TIME Organization

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