Principal Data Scientist
Tasks
- Apply AI quality practices including evaluation and red teaming
- Coordinate with governance security and legal stakeholders
- Create prompt and agent templates and evaluation harnesses
- Define technical vision and architecture direction
- Design production-grade AI systems
- Develop agentic AI capabilities with tool use and orchestration
- Establish reusable AI standards and reference architectures
- Guide prototypes and pilots to production AI
- Implement model and agent observability and monitoring
- Lead implementation of generative and agentic AI solutions
- Mentor data scientists and AI engineers
- Provide hands on technical leadership for AI adoption
- Serve as senior technical reviewer for AI use cases
- Stay current with emerging AI technologies
- Translate business needs into measurable AI solutions
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | AWS | AWS Bedrock | Agent Orchestration | Bias and fairness | By Design | CI/CD | Cost Tracking | CrewAI | Human-in-the-loop | LLMOps | Langchain | Langgraph | MLOps | Model Cards | Model Evaluation | Observability | Performance Monitoring | Privacy by Design | Python | RAG | Red Teaming | Regression testing | Retrieval-Augmented Generation | Security guardrails | Testing | The Loop | Tool-Calling | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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