LLM Platform Engineer/Lead
Tasks
- Build LLM integration frameworks
- Create AI observability and monitoring
- Design standardized LLM workflows
- Develop SDKs and shared libraries
- Enable product integration of AI features
- Establish AI safety practices
- Implement prompt management systems
- Optimize reliability, scalability, and cost
- Own AI tooling from experimentation to deployment
- Set up evaluation pipelines
Perks/Benefits
- Annual learning and development budget
- Career growth
- Flexible remote work
- High visibility with senior leadership
- Home office setup budget
- International team collaboration
Skills/Tech-stack
AI guardrails | AI orchestration | AI orchestration frameworks | API Design | AWS | Anthropic API | Azure | CI/CD | Cloud Platforms | Data Lake | Data Warehouse | Distributed Systems | Docker | ETL | Embeddings | Evaluation | Fine Tuning | GCP | Moderation systems | Monitoring | Observability | OpenAI API | Orchestration frameworks | Prompt engineering | Prompt versioning | Python | RAG | Service architecture | Telemetry | Tokenization | Vector Database | Vector Search
Education
N/A
Roles
AI | AI Platform Engineer | Engineer | LLM Platform Engineer | Platform Engineer
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