AI Engineer – AI Engineering & Platforms (AI Centre of Excellence)
Tasks
- Apply security privacy and safety controls
- Build AI services and components
- Build REST and GraphQL APIs
- Create retrieval-augmented generation solutions
- Deploy and manage AI services with Docker and Kubernetes
- Design AI solution architecture
- Develop data grounding strategies with vector search
- Develop reusable AI libraries APIs and services
- Implement LLM based workflows and agents
- Implement evaluation and testing for AI components
- Implement infrastructure as code with Terraform
- Implement logging, metrics, and tracing
- Implement prompt and system design
- Integrate AI with NodeJS backends and React frontends
- Set up CI CD pipelines for AI services
Perks/Benefits
- N/A
Skills/Tech-stack
Access Control | Automated testing | Azure | Azure OpenAI | CI/CD | DBT | Docker | Evaluation testing | Event Driven | Event-driven architecture | Feature Stores | Git | Google AI | Google Cloud | GraphQL | Infrastructure as Code | JavaScript | Kubernetes | Logging | MLOps | Metrics | Microservices | Model registries | Node.js | Observability | Prompt engineering | Python | REST | React | Retrieval-Augmented Generation | Snowflake | Terraform | Tracing | TypeScript | Vector Search | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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