Principal AI Engineer
Tasks
- Build and scale data pipelines
- Build observability for data systems
- Create technical proposals specifications and documentation
- Define data contracts and standards
- Design and build data infrastructure
- Drive privacy compliant data capture strategy
- Establish data quality governance and lineage
- Mentor engineers on data architecture and AI infrastructure
- Own agentic product data layer
- Own platform wide data architecture
Perks/Benefits
- 25 holiday days per year
- Company health plan
- Company training budget
- Group life insurance
- Professional development budget
- Real influence over technical direction
- Remote-first culture
- Sabbatical leave
Skills/Tech-stack
AI orchestration | AWS Kinesis | AWS Lambda | Agentic Systems | Amazon EKS | Amazon Redshift | Amazon SNS | Amazon SQS | Analytics | Batch Processing | CI/CD | Caching | Canary deployments | Data Architecture | Data Contracts | Data Governance | Data Lineage | Data Modeling | Data Pipelines | Data Quality | Data Warehousing | Datadog | DevOps | Distributed tracing | DocumentDB | ElastiCache | Elasticsearch | Feature Flags | Fullstack development | GDPR | Gradual Rollouts | Guardrail design | Jailbreaks | Kubernetes | LLMs | Low Latency | Metrics monitoring | Model Context Protocol | MongoDB | MySQL | Node.js | Operational Databases | Output Validation | PII handling | PostgreSQL | Prompt injection | Recommendation Systems | Redis | SLOs | Search | Sentry | Streaming Data | Structured Logging | Terraform | TypeScript
Education
N/A
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