Forward Deployed Engineer – AI Inference

FriendliAI

. Assist enterprises in deploying, scaling, and operating generative and agentic AI workloads on FriendliAI infrastructure .

Posted 10/8/2026full-timeSan Francisco • California • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and managing generative AI workloads on cloud infrastructure, with a strong focus on Kubernetes, Docker, and Terraform. Proven ability to collaborate with DevOps teams and implement scalable solutions while ensuring platform reliability and performance optimization.

Highest-signal resume keywords

KubernetesDockerTerraformGenerative AI Model ServingCloud Infrastructure

ATS Keywords

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Hard Skills

Cloud InfrastructureDevOpsDistributed SystemsPerformance TuningGPU-Based ComputingBackend SystemsLarge Model DeploymentInference FrameworksNetworking SecurityHybrid-Cloud Deployments

Soft Skills

Problem-SolvingDebugging

Tools & Technologies

AWSGCPOCIHelmPrometheusGrafanaLokiELKOTELTriton

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster's Degree in Computer EngineeringElectrical Engineering

Industry Keywords

CI/CD WorkflowsObservabilityPlatform ReliabilityScaling StrategiesSOC 2 Compliance

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerGoogle Cloud PlatformGrafanaKubernetesPrometheusTerraform

About the role

Key responsibilities & impact

Assist enterprises in deploying, scaling, and operating generative and agentic AI workloads on FriendliAI infrastructure
Work directly with customers to solve and implement production-grade applications using Serverless Endpoints, Dedicated Endpoints, or Container
Design and implement large-scale deployment architectures for LLM and multimodal inference
Deploy and manage containerized workloads across Kubernetes clusters
Diagnose production issues, including performance bottlenecks, and implement temporary fixes as needed
Collaborate with customers’ DevOps teams to integrate FriendliAI’s infrastructure into CI/CD workflows
Develop scripts, Helm charts, and Terraform modules to simplify repeated deployments
Contribute field insights to platform reliability, observability, and scaling strategies
Lead workshops, technical sessions, or webinars to help customers master infrastructure best practices

Requirements

What you’ll need

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

Benefits

Comp & perks

Competitive compensation and benefits package
Daily lunch and dinner provided
Unlimited snacks and beverages
Health check-up
Top-tier hardware support
Flexible working hours
Highly collaborative environment