Solutions Architect - AI Inference Specialist

FriendliAI; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation and benefits package

Daily lunch and dinner

Unlimited snacks and beverages

Health check-up

Flexible working hours

Job summary

FriendliAI is looking for a Solution Architect in San Francisco to enable enterprises to implement AI workloads effectively. The role involves designing large-scale deployment architectures, solving AI inference challenges, and collaborating closely with customers' DevOps teams. Ideal candidates will have 3+ years in cloud infrastructure or DevOps, strong skills in Kubernetes, Docker, Terraform, and a solid understanding of distributed systems. Benefits include competitive compensation, flexible hours, and daily meals.

Qualifications

• 3+ years of experience in cloud infrastructure, DevOps, or reliability engineering.
• Strong foundation in distributed systems, networking, and performance tuning.
• Experience with GPU-based computing and generative AI model serving workloads.

Responsibilities

• Design and implement large-scale deployment architectures for LLM and multimodal inference.
• Deploy and manage containerized workloads across Kubernetes clusters.
• Collaborate with customers' DevOps teams to integrate FriendliAI’s infrastructure into their CI/CD workflows.
• Lead workshops and technical sessions for customers.

Skills

cloud infrastructure

DevOps

reliability engineering

Kubernetes

Docker

Terraform

Helm

distributed systems

problem-solving

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Kubernetes

Docker

Terraform

Helm

Job description

About the job

FriendliAI is seeking a Solution Architect 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.

Key Responsibilities

• 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.

Qualifications

• 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

• 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 us

FriendliAI is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure powers high-throughput, low-latency workloads for global organizations and integrates directly with Hugging Face, providing instant access to over 500,000 open-source models. We are on a mission to deliver the world’s best platform for AI inference.