Senior AI Platform Engineer
Tasks
- Build secure integrations using APIs
- Define AI deployment observability evaluation monitoring standards
- Design and build reusable platform capabilities for LLM applications
- Develop developer tooling and SDKs
- Develop scalable data and knowledge pipelines
- Ensure security privacy governance access control compliance
- Evaluate AI models and infrastructure technologies
- Evolve platform architecture and engineering standards
- Measure AI quality accuracy latency reliability security cost
- Move AI from prototyping to production deployment
- Promote data engineering and operational reliability practices
- Translate business needs into practical technical solutions
Perks/Benefits
- Asynchronous collaboration
- Distributed international team
- Flexible parental leave
- Fully remote
- Mental health support
- Paid time off
- Professional growth
- Technical ownership
- Wellbeing allowance
- Work from home flexibility
- Work from home stipend
Skills/Tech-stack
AI Agents | API | AWS | AWS Bedrock | Access Control | Airflow | Authentication | Authorization | Cloud infrastructure | DBT | Data Governance | Data Modeling | Data Pipelines | Data Quality | Databricks | Embeddings | Evaluation | Generative AI | LLM | Langchain | Langgraph | MCP | Monitoring | Observability | Python | RAG | SQL | Snowflake | Tool-Calling | Vector Databases | Vector Search
Education
N/A
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