AI Infrastructure Engineer
ILS 420K-504K (estimate) Mid-level Full Time
Tasks
- Add LLM tracing and evaluation pipelines
- Architect AWS Kubernetes platform for AI agents
- Build infrastructure as code with Terraform
- Define SLOs, SLIs, and error budgets
- Design and deploy production agents and multi agent pipelines
- Implement cost controls with FinOps practices
- Implement guardrails for prompt injection defense
- Implement observability with OpenTelemetry and Prometheus
- Integrate agent workflows via APIs databases webhooks and Slack
- Maintain audit trails
- Manage incidents and postmortems
- Own GitOps and CI CD pipelines
- Own agent lifecycle from scoping to monitoring and iteration
- Redact PII and enforce model allowlists
- Route models by cost and optimize caching
- Set up human in the loop checkpoints
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | Agent SDK | Amazon Web Services | Anthropic Agent SDK | Argo CD | Audit Trail | Batch Processing | CI/CD | Caching | Claude Code | Cost Optimization | Error Budgets | FinOps | GitHub Actions | GitOps | Human-in-the-loop | IAM | Incident Response | Injection Defense | Kubernetes | LLM Evaluation | LLM tracing | Langfuse | MCP | Model Allowlist | Model routing | Observability | OpenTelemetry | PII Redaction | Prometheus | Prompt injection | Prompt injection defense | Python | REST API | Real Time | Real-time Processing | SLO/SLI | Terraform | The Loop | Time processing | Token metrics | Vector Database | Web Services
Education
N/A
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