AI Engineer - Cloud
Tasks
- Build CI/CD pipelines in Azure DevOps
- Collaborate with stakeholders to design solutions
- Deploy and test LLM applications
- Develop GenAI gateway on Azure
- Integrate AI into business processes IT systems data platforms
- Integrate LLM providers
- Manage LLM lifecycle
- Operationalize AI capabilities
Perks/Benefits
- Discounted products and services
- Flexible working hours
- Home office setup
- Home working allowance
- Pension plan
- Training budget
- Travel reimbursement
- Work-life balance
Skills/Tech-stack
AI Search | AKS | API Keys | API Management | ARM Templates | Active Directory | Anthropic Claude | Application Insights | Azure AI | Azure AI Search | Azure Active Directory | Azure DevOps | Azure Monitor | Best practices | Bicep | CI/CD | Code Reviews | Docker | Event Driven | Event-driven architecture | Infrastructure as Code | Kubernetes | LLM Gateway | Langchain | Language Models | Large Language Models | Llama | Message Queues | Microsoft Azure | Mistral | OAuth2 | Observability | OpenAI | Python | REST | Security best practices | Streaming APIs | Terraform | Testing | Vector Databases | WebSockets | “as-code”
Education
Roles
AI | AI Engineer | AI Platform Engineer | AI/ML Engineer | Cloud Engineer | Cloud) | Engineer | ML Engineer | Platform Engineer
Regions
Countries
States
Cities
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