Ai全栈开发工程师
Tasks
- Build and iterate agent platform workflow orchestration
- Build enterprise RAG with data ingestion chunking indexing and permissions filtering
- Build evaluation datasets and online observability with tracing metrics and logs
- Define JSON schema parameters and implement authentication and tenant isolation
- Deliver React user and admin interfaces with state management
- Develop Python backend APIs queues scheduling permissions and auditing
- Develop agent tool framework engineering with versioning and compatibility
- Engineer SaaS multi tenant quotas and offline private deployment packages
- Implement A B testing and regression gating
- Implement hybrid retrieval reranking and citation provenance
- Implement idempotency retry rate limiting failure fallback and audit replay
- Implement model routing and provider adapter layer with degradation and disaster recovery
- Implement multi agent collaboration and task system
- Optimize latency and cost with caching batching and concurrency control
- Set up Kubernetes Helm and Docker Compose deployment and offline dependency distribution
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ABAC | Asynchronous programming | Audit Logging | Authentication | Authorization | B testing | Concurrency | Docker Compose | Elasticsearch | FastAPI | HITL | Helm | Hybrid search | Idempotency | JSON Schema | K8s | Kubernetes | Langgraph | Logging | Metrics | Milvus | Multi-tenant | Multi-tenant architecture | PGVector | Performance optimization | Pydantic | Python | RBAC | Rate Limiting | React | Reranking | Retrieval-Augmented Generation | Retry) | System design | Task Queue | Tenant architecture | Tracing | Vector Search
Education
N/A
Roles
AI | AI Engineer | Developer | Engineer | Full Stack | Full Stack Developer
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