Tasks:
- * Analyze features and risk data
- * Assist strategy generation and deployment
- * Build AI risk-control workflows and applications
- * Deploy stable AI applications
- * Develop risk knowledge bases and analysis assistants
- * Evaluate risk strategy effectiveness
- * Implement agent-based risk analysis tools
- * Implement tool permissions and audit trails
- * Improve model and tool-call performance
- * Integrate risk data and business systems through MCP
- * Monitor and optimize workflow reliability
- * Support anomaly discovery and risk attribution
- * Support case handling and complaint analysis
- * Translate business problems into AI workflows
Perks/Benefits:
Skills/Tech stack required:
[Access Control] [Agent Frameworks] [API Development] [Autogen] [C++] [Containerization] [Data Analysis] [Database Development] [Data Processing] [Exception Handling] [Function Calling] [Git] [Go] [Information Retrieval] [Java] [Langchain] [Langgraph] [Linux] [Llamaindex] [Logging and auditing] [MCP] [Memory Management] [Model Evaluation] [Prompt engineering] [Python] [RAG] [Rust] [Service observability] [SQL] [Workflow Orchestration]
Educational requirements:
N/A
Role(s):
[AI Engineer] [Engineer] [Software Engineer]