AI & Data Architect, US
Tasks
- Architect NL2SQL and conversational analytics systems
- Architect agent runtimes and multi agent orchestration
- Architect multimodal AI experiences
- Build AI ready data platform architectures
- Define AI evaluation and observability frameworks
- Define canonical APIs and integration standards
- Define long term AI and data architecture strategy
- Define semantic architecture for structured and enterprise knowledge
- Design AI security and governance controls
- Design enterprise knowledge management architectures
- Design scalable generative AI platform architectures
- Establish reusable integration patterns across OCI and Oracle products
- Evaluate emerging AI and data technologies
- Implement retrieval augmented generation systems
- Mentor engineers and drive technical direction
- Select retrieval architecture options and ranking strategies
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agent Orchestration | Agentic AI | Asynchronous Workflows | Audit Logging | Authentication | Authorization | CDC | Change Data Capture | Cloud Native | Cloud Native Architecture | Containers | Data Capture | Data Lakes | Data integration | Distributed Systems | Embeddings | Encryption | Enterprise Search | Event Driven | Event-driven architecture | Fine Tuning | Generative AI | Graph Databases | Hybrid search | Injection Defense | Injection Protection | KPI evaluation | Knowledge graphs | Kubernetes | LLM Inference | Lakehouse | Language Models | Large Language Models | Linux | Metadata governance | Microservices | Model Fine-tuning | Model routing | Multi-Agent | Multi-agent orchestration | Networking | Non-relational | Non-relational Databases | Observability | Prompt injection | Prompt injection defense | Prompt-injection protection | RAG | Relational databases | Retrieval-Augmented Generation | Secrets management | Service security | Service to Service | Service to Service Security | Streaming Data | Tool use | Vector Search
Education
Roles
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