Solutions Architect - AI Inference Specialist
FriendliAI6 months ago
San Francisco, CA, USAMid Level
Responsibilities
- 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.
- Collaborate with customer DevOps teams to integrate FriendliAI infrastructure into their workflows.
- Develop scripts, Helm charts, and Terraform modules to simplify repeated deployments.
- Provide field insights for platform reliability, observability, and scaling strategies.
- Lead customer workshops, technical sessions, and webinars on infrastructure best practices.
Requirements
- At least 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.
- Strong problem-solving and debugging skills in real-world environments.
- Preferred experience deploying large LLMs or diffusion models on GPUs or clusters.
- Preferred familiarity with Triton, vLLM, TensorRT, DeepSpeed-Inference, Prometheus, Grafana, Loki, ELK, and OTEL.
- Understanding of networking security and compliance frameworks such as SOC 2.
- Experience supporting on-premises or hybrid-cloud deployments.
Benefits
- Competitive compensation and benefits package.
- Daily lunch and dinner provided, with unlimited snacks and beverages.
- Health check-up and top-tier hardware support.
- Flexible working hours and a highly collaborative environment.
Tech Stack
Categories
Solutions Engineering