AI Engineer – AI Engineering & Platforms (AI Centre of Excellence)
Tasks
- Apply Infrastructure as Code with Terraform
- Build AI services and components
- Build Retrieval-Augmented Generation solutions
- Build data pipelines for AI grounding
- Create prompt and system designs
- Deploy AI services using MLOps practices
- Design AI solution architecture
- Design evaluation and testing for AI systems
- Develop reusable AI APIs and libraries
- Ensure logging, metrics, and tracing
- Implement CI/CD pipelines
- Implement LLM based workflows and agents
- Implement security privacy and safety controls
- Implement vector search with embeddings
- Integrate AI platforms with NodeJS and React
- Integrate LLMs with tools and function calling
- Support production delivery and monitoring
- Use Docker and Kubernetes for orchestration
Perks/Benefits
- N/A
Skills/Tech-stack
Apollo Server | Automated testing | Azure | Azure OpenAI | CI/CD | DBT | Docker | Embeddings | Event Driven | Event-driven architecture | Express | Git | Google Cloud | GraphQL | Guardrails | JavaScript | Kubernetes | Logging | MLOps | MLOps pipelines | Metrics | Microservices | Model Evaluation | NestJS | Node.js | Privacy | Prompt engineering | Python | REST | React | Retrieval-Augmented Generation | Security | Snowflake | Terraform | Tracing | TypeScript | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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