Senior AI Engineer
Tasks
- Continuously optimize AI solutions using performance measurement and feedback
- Define engineering standards and reference architectures
- Design and execute AI evaluation testing and experimentation
- Design and maintain cloud native enterprise applications
- Design deploy and operate AI platforms on Azure
- Develop and implement LLM and RAG based solutions
- Ensure security privacy governance compliance and responsible AI requirements
- Evaluate AI technologies for business impact
- Implement CI/CD and Infrastructure as Code
- Implement logging monitoring alerting governance and secure environments
- Lead design and delivery of scalable AI solutions
- Manage AI application and model lifecycle monitoring and release
- Provide technical leadership mentorship and engineering best practices
- Translate business needs into production ready AI systems
Perks/Benefits
- Access to learning university
- Annual paid leave
- Hybrid work model
- Remote work flexibility
- Volunteering days
Skills/Tech-stack
APIs | Agile | Alerting | Azure | Azure DevOps | CI/CD | Distributed Systems | Docker | Infrastructure as Code | Kubernetes | LLMs | Logging | MLOps | Machine Learning | Monitoring | Observability | Python | RAG | Secure Software | Secure software design | Software Design | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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