Senior AI Deployment Engineer
C
CI&TAI deployment
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- KubernetesCI/CDDevOpsTerraform
Requirements
- Knowledge of LLMOps.
- Knowledge of DevOps engineering.
- Knowledge of Site Reliability Engineering (SRE).
- Knowledge of AI security and access control.
- Knowledge of observability and monitoring.
- Knowledge of AI FinOps and cost optimization.
- Knowledge of guardrails and AI safety.
- Knowledge of CI and CD.
- Knowledge of model routing and selection.
- Nice to have: cloud computing concepts.
- Nice to have: applied infrastructure as code (Terraform).
- Nice to have: Azure Container Apps, scalability, connectivity, code review, and Kubernetes containers.
Responsibilities
- Design CI/CD pipelines for agentic environments and reduce the time between building and delivery.
- Deploy conventional applications using app stores, CDNs, mobile release trains, feature flags, and blue/green service rollouts.
- Provision and automate standardized development, staging, and production environments.
- Operate model and agent serving to ensure availability, latency, and scale in production.
- Establish quality, security, and compliance pipeline gates before release.
- Manage versioning and release cadence, and run rollback and fast recovery procedures.
- Instrument observability and monitor solution behavior, quality, and token costs; optimize inference budgets and model routing.
- Secure production solutions through access control, data protection, and AI risk mitigation.
- Apply infrastructure guardrails and version application packages, environment configurations, and model endpoints.
- Feed production signals on cost, failures, and performance back to the AI Engineer and delivery process.
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