[Job - 32512] Senior - AI Deployment Engineer, Brazil

CI&T, Brazil

What you will do

- Take the solution to production, designing CI/CD pipelines for agentic environments and reducing the time between building and delivering (lead time).
- Execute the deployment of conventional applications (app stores, CDN, mobile release trains, feature flags and blue/green service rollouts), to bring any product to the client safely.
- Provision and automate the standardized configuration of the dev, staging and production environments.
- Operate the serving of models and agents, ensuring availability, latency and scale in production.
- Establish quality, security and compliance pipeline gates at every stage of the delivery line before release.
- Execute versioning strategies, manage the release cadence and run rollback and fast recovery procedures in case of failure.
- Instrument observability and metrics over the AI solution, monitoring behavior, quality and token cost. Manage the AI FinOps of the operation, optimizing the inference budget and the intelligent routing of models (smaller ones for simple tasks, larger ones only when necessary), to improve the cost-performance ratio in production.

CI&T, Brazil

- Take the solution to production, designing CI/CD pipelines for agentic environments and reducing the time between building and delivering (lead time).
- Execute the deployment of conventional applications (app stores, CDN, mobile release trains, feature flags and blue/green service rollouts), to bring any product to the client safely.
- Provision and automate the standardized configuration of the dev, staging and production environments.
- Operate the serving of models and agents, ensuring availability, latency and scale in production.
- Establish quality, security and compliance pipeline gates at every stage of the delivery line before release.
- Execute versioning strategies, manage the release cadence and run rollback and fast recovery procedures in case of failure.
- Instrument observability and metrics over the AI solution, monitoring behavior, quality and token cost. Manage the AI FinOps of the operation, optimizing the inference budget and the intelligent routing of models (smaller ones for simple tasks, larger ones only when necessary), to improve the cost-performance ratio in production.