Senior AI Platform Engineer
Tasks
- Build secure integrations using APIs
- Contribute to platform architecture and engineering standards
- Deploy AI capabilities from prototyping to production
- Design and build reusable platform capabilities for LLM applications
- Develop reusable frameworks libraries services SDKs and developer tooling
- Develop scalable data and knowledge pipelines
- Ensure AI platform compliance with security privacy authentication authorization and data governance
- Establish standards for AI deployment observability evaluation monitoring and lifecycle management
- Evaluate emerging AI models and frameworks for business value
- Measure AI quality accuracy latency reliability security and cost
- Translate business needs into practical technical solutions
Perks/Benefits
- Asynchronous collaborative model
- Distributed international working environment
- Flexible parental leave
- Fully Remote Working Environment
- Mental health and wellbeing support
- Monthly Wellbeing Allowance
- Paid time off
- Work from anywhere within permitted locations
- Work from home stipend
Skills/Tech-stack
AI Agents | AI Observability | APIs | AWS Bedrock | Access Control | Apache Airflow | Authentication | Authorization | Cost Optimization | DBT | Data Governance | Data Modeling | Data Pipelines | Data Quality | Databricks | Embeddings | Generative AI | LLM Evaluation | Langchain | Langgraph | Language Models | Large Language Models | Model Context Protocol | Monitoring | Python | Retrieval-Augmented Generation | SQL | Security | Snowflake | Tool-Calling | Vector Databases | Vector Search
Education
N/A
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