Key skills
AWSAzureCloudGoogle Cloud PlatformAIMLLLMMLOpsData EngineeringGCPGoogle CloudCommunicationCollaborationRemote Work
About this role
Role Overview
- Evaluate architecture of AI solutions, models and agents
- Support the definition of technical standards and monitoring controls
- Establish and implement observability for AI systems
- Implement technical metrics (performance, drift, security)
- Support technical validation processes for committees
- Ensure traceability and versioning of models
Requirements
- Degree in Engineering, Computer Science or a related field
- Hands-on experience with:
- AI/ML platforms
- APIs, models and agents
- Courses in MLOps, Responsible AI, and AI Security
- Desirable certifications:
- Cloud (AWS, Azure, GCP)
- Certifications in ML or Data Engineering
- Technical skills:
- AI, ML and LLM architecture
- Model and pipeline monitoring
- Familiarity with MLOps and observability
- Security and access control
- Interpersonal skills:
- Clear technical communication
- Collaboration with engineering and data teams
- Ability to translate technical complexity into governance
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
Benefits
- 14th and 15th fixed salaries
- Profit-sharing (based on seniority)
- Health and Dental plan with no co-payment
- Wellness programs via Wellhub (formerly Gympass) including Nutrition, Psychology, Occupational Health, Massage, running group and local gym access
- Meal Allowance and Food Voucher – flexible percentage allocation between VA/VR cards, no co-payment
- Extended maternity and paternity leave
- Childcare or nanny assistance for children up to 6 years and 11 months
- Assistance for children with disabilities, no age limit
- Life insurance
- Private pension up to 7% of salary
- Training platform – Sicredi Aprende, with a variety of courses
- 40-hour workweek – operated via a time bank system
- Remote work allowance (except for positions requiring 100% on-site presence)