Senior Site Reliability Engineer
Skills
- Production Kubernetes experience (EKS, GKE, AKS)
- Cloud proficiency in AWS, Azure, or GCP
- Strong Python programming; familiarity with Bash, Go, or PowerShell
- Infrastructure-as-Code (Terraform, CloudFormation)
- CI/CD and GitOps (ArgoCD, Flux) workflows
- Containerization (Docker) and Kubernetes Operators/Helm
- Observability tooling (Prometheus, Grafana, ELK/EFK, Langfuse)
- Experience building AI/ML/LLM pipelines (RAG, fine-tuning, inference)
- SLI/SLO/SLA-driven reliability engineering and incident response
Responsibilities
- Design, deploy, and scale AI/ML/LLM infrastructure across cloud providers (AWS, Azure, GCP) for high reliability and performance.
- Manage and optimize Kubernetes environments (EKS, AKS, GKE) for AI services, data pipelines, and model operations.
- Build and automate end-to-end data and model pipelines for fine-tuning, inference, and RAG workloads using Terraform, Python, and CI/CD tooling.
- Implement GitOps and CI/CD pipelines, containerization best practices (Docker/Kubernetes), and infrastructure-as-code.
- Implement monitoring, observability, and reliability practices using Prometheus, Grafana, ELK/EFK, Langfuse, and SLI/SLO/SLA frameworks.
- Lead incident response, performance tuning, capacity planning, and cost optimization for AI infrastructure and production workloads.
- Collaborate with ML, platform, and security engineering teams to enable continuous delivery of models and applications at scale.
Education
- Bachelor's or Master’s degree in Computer Science, Engineering, or related field, or equivalent experience
Benefits
- Competitive base salary plus discretionary bonus
- Equity grants / stock options
- Medical, dental, and vision insurance
- 401(k) or regional retirement plans
- Flexible and remote-friendly work arrangements
- Paid time off, parental leave, and holidays
- Professional development and conference support
- Inclusive culture and distributed team with occasional in-person events
Average salary estimate
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