AI Engineer, Product Analytics
Tasks
- Build data pipelines for agent datasets
- Contribute to data modeling for LLM reasoning
- Design proactive monitoring intelligence systems
- Evaluate model performance with testing and sampling
- Implement tool calling integrations
- Integrate LLM APIs into analytics agents
- Maintain prompts and context for changing data rules
- Monitor production agents for quality drift
- Perform root cause analysis on agent failures
- Refactor prototypes into production components
- Translate business requirements into agent designs
Perks/Benefits
- Flexible vacation
- Flexible work arrangements
- Headspace app access
- Hybrid work model
- Mental health days
- Retirement savings
- Tuition reimbursement
- Two paid volunteer days off annually
- Work from anywhere up to 8 weeks per year
Skills/Tech-stack
A/B | A/B Testing | AWS | Azure | B testing | Data Modeling | Docker | Embeddings | Experiment design | GCP | Guardrails | LLM | LLMOps | Logging | MLOps | Monitoring | Observability | Prompt engineering | Python | RAG | Retrieval Pipelines | SQL | Semantic Search | Telemetry | Tool-Calling | Unit Testing | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer
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