AI Engineer – AI Engineering & Platforms (AI Centre of Excellence)
Tasks
- Apply observability logging metrics tracing
- Build AI services and components
- Build data grounding strategies
- Collaborate with product and data teams
- Contribute to AI platform tooling
- Create evaluation and testing for AI
- Create prompts and system design
- Define evaluation testing for quality safety and fairness
- Deploy AI services with Docker and Kubernetes
- Design AI solution designs
- Develop data pipelines for AI use cases
- Develop reusable AI libraries and APIs
- Enforce access control and guardrails
- Implement CI/CD pipelines
- Implement LLM workflows and agents
- Implement retrieval-augmented generation
- Implement security privacy and safety controls
- Implement vector search and embeddings
- Integrate tool function calling
- Manage infrastructure as code with Terraform
Perks/Benefits
- N/A
Skills/Tech-stack
Access Control | Azure OpenAI | CI/CD | DBT | Docker | Embeddings | Evaluation | Event Driven | Event-driven architecture | Function Calling | Git | GitHub | Google AI | GraphQL | Guardrails | JavaScript | Kubernetes | LLM | Logging | MLOps | Metrics | Microservices | Observability | Prompt engineering | Python | RAG | REST APIs | Retrieval-Augmented Generation | Snowflake | System design | TDD | Terraform | Tool-Calling | Tracing | TypeScript | Vector Search
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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