Senior AI Engineer
Buenos Aires, Argentina
CAD 123K-170K (estimate) Senior-level Full Time
Tasks
- Apply mlops best practices for deployments
- Build agentic AI solutions
- Communicate AI systems to stakeholders
- Deploy AI solutions to cloud platforms
- Design develop and deploy AI workflows
- Ensure ai agent operations with observability and monitoring
- Evaluate agent autonomy performance and safety
- Implement evaluation frameworks for ai performance metrics
- Implement multi-agent systems
- Integrate generative ai models with api and databases
- Optimize prompts and context for ai tasks
- Orchestrate ai model selection tuning and validation
- Use ci cd to streamline deployment pipelines
Perks/Benefits
Skills/Tech-stack
AI Services | API Integration | AWS Bedrock | AWS CodeDeploy | Agent systems | Agentic AI | Amazon Web Services | Azure AI | Azure AI Services | Azure Pipelines | Braintrust | CI/CD | Chunking | Cloud platform | Containers | Context engineering | DeepEval | Django | Embeddings | Evaluation Frameworks | Express | Function Calling | Generative AI | GitHub Actions | Google Cloud | Google Cloud Platform | Java | Jenkins | Kubernetes | Langsmith | Language Models | Language Processing | Large Language Models | MCP | MLOps | Model Context Protocol | Monitoring | Multi-Agent | Multi-Agent Systems | NLP | Natural Language | Natural Language Processing | Observability | OpenAI Eval | Orchestration | Prompt engineering | Python | RAG | Ragas | Retrieval-Augmented Generation | Spring | TypeScript | Vector Databases | Web Services
Education
N/A
Roles
Regions
Countries
States
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