Software Engineer, Site Reliability Engineer

About Us:

Here at Fireworks, we’re building the future of generative AI infrastructure. Fireworks offers the generative AI platform with the highest-quality models and the fastest, most scalable inference. We’ve been independently benchmarked to have the fastest LLM inference and have been getting great traction with innovative research projects, like our own function calling and multi-modal models. Fireworks is funded by top investors, like Benchmark and Sequoia, and we’re an ambitious, fun team composed primarily of veterans from Pytorch and Google Vertex AI.

The Role:

We’re seeking a highly skilled SRE/PE with deep expertise in Kubernetes (k8s), cloud networking, and infrastructure automation. This role will focus on reducing incident response time, implementing auto-remediation, optimizing auto-scaling, and improving cluster efficiency and service health. You’ll design systems that balance performance, cost, and reliability while working onsite at our Redwood City or New York City team.

Key Responsibilities:

1. Incident Response & Reliability Engineering:

   • Drive initiatives to reduce incident response time through improved monitoring, alerting, and automated remediation.

   • Build self-healing systems and playbooks for common failure scenarios.

   • Lead blameless post-mortems and implement preventative measures.

2. Kubernetes & GPU Cluster Optimization:

   • Manage and optimize GPU-enabled Kubernetes clusters for AI/ML workloads, focusing on cost-performance efficiency, auto-scaling, and resource utilization.

   • Debug performance bottlenecks in distributed systems (e.g., network, storage, GPU scheduling).

3. Cloud Networking & Service Health:

   • Strengthen service health by refining cloud networking stacks (VPCs, load balancers, service meshes) and ensuring low-latency communication.

   • Design fault-tolerant architectures to minimize downtime.

4. Monitoring & Observability:

   • Enhance service monitoring with tools like Prometheus, Grafana, and custom metrics pipelines.

   • Implement predictive analytics to proactively address system health risks.

5. Automation & Infrastructure-as-Code (IaC):

   • Build automation for cluster provisioning, scaling, and recovery using Terraform, Argo, and CI/CD pipelines.

   • Develop tools to streamline operational workflows (e.g., automated rollbacks, canary deployments).

Minimum Qualifications:

• 3+ years in SRE/PE/DevOps roles with production-grade Kubernetes experience.

• Proficiency in cloud networking (AWS/GCP/Azure VPCs, firewalls, DNS) and service monitoring (Prometheus, Alertmanager, Grafana).

• Hands-on experience with incident management and improving system reliability/SLOs.

• Strong scripting/coding skills (Python/Go/Bash) for automation and tooling.

• Familiarity with object storage (S3, GCS) and data pipeline integration.

Preferred Qualifications:

• Experience with GPU clusters (NVIDIA GPUs, MIG, CUDA) and AI/ML workloads.

• Knowledge of auto-scaling technologies (K8s HPA/VPA) and auto-remediation frameworks.

• Expertise in service meshes (Istio)

Why Fireworks AI?

• Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.

• Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.

• Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.

• Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.