Ai全栈开发工程师
Tasks
- Build agent platform workflows
- Build enterprise RAG pipelines
- Create offline evaluation datasets
- Deploy private installation with Kubernetes Helm and Docker Compose
- Design request idempotency retry and rate limiting
- Develop FastAPI backend APIs and queues and scheduling
- Develop React user and admin interfaces
- Develop conversation and task system
- Enforce ACL RBAC and ABAC access control
- Engineer SaaS multi tenant quotas
- Engineer agent tool registry and versioning
- Generate reproducible debugging scripts
- Implement authentication and tenant isolation
- Implement chunking and indexing
- Implement citation provenance
- Implement concurrency and token budgeting
- Implement failure downgrade and fallback
- Implement hybrid search with re ranking
- Implement incremental updates
- Implement model fallback disaster recovery
- Implement model provider adapter and routing
- Implement multi-agent collaboration
- Implement online metrics and A B testing
- Implement replay and audit
- Implement tracing and metrics and logs for observability
- Implement upgrade migration and rollback plans
- Integrate document and database and Elasticsearch sources
- Manage memory and context
- Optimize cost and latency with caching and batching
- Package offline dependencies and models
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ABAC | ACL | Asynchronous programming | Audit Logging | Authentication | B testing | Concurrent programming | Docker | Docker Compose | Elasticsearch | FastAPI | Helm | Hybrid search | Idempotency | JSON Schema | Kubernetes | Langgraph | Logging | Metrics | Milvus | Multi-tenancy | Offline deployment | PGVector | Performance optimization | Pydantic | Python | RAG | RBAC | Rate Limiting | Re-ranking | React | Retry) | State Machine | System design | Task Queue | Tracing | Vector Database
Education
N/A
Roles
AI | AI Engineer | Developer | Engineer | Full Stack | Full Stack Developer
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