Senior AI Engineer
Tasks
- Apply privacy and consent controls
- Build AI services and pipelines
- Build automated ML and LLM delivery pipelines
- Define evaluation and monitoring for generative AI
- Deploy AI models as APIs and jobs
- Design AI solution architectures
- Embed AI governance into engineering workflows
- Ensure auditability and regulatory traceability
- Establish model versioning and reproducibility standards
- Implement agent workflows
- Implement batch and real time AI pipelines
- Implement data classification and handling controls
- Implement embeddings and semantic search
- Implement retrieval-augmented generation
- Implement security and access controls for AI
- Mentor engineers and share technical knowledge
- Run production incident troubleshooting for AI systems
Perks/Benefits
Skills/Tech-stack
Agentic AI | Alerting | Azure | Cloud platform | Data Governance | Embeddings | Google Cloud | Google Cloud Platform | LLMOps | Logging | MLOps | Machine Learning | Model Risk Management | Model risk | Model versioning | Monitoring | Observability | Privacy | Python | Reliability Engineering | Reproducibility | Retrieval-Augmented Generation | Risk Management | SQL | Scalability | Security | Semantic Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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