Principal AI Flow Development Engineer
Tasks
- Architect multi-agent systems
- Build ETL workflows for document parsing chunking and enrichment
- Build agent to agent integrations with enterprise workflows
- Build observability for tracing token usage and latency
- Build prompt systems and orchestration logic
- Design retrieval pipelines for IP documentation
- Develop APIs for agent interaction with EDA tools
- Document architecture and integration patterns
- Establish evaluation frameworks for retrieval and agent success
- Implement AI copilots with tool use
- Implement guardrails for hallucination detection and output validation
- Implement model context protocol servers and clients
- Optimize cost and performance with caching model routing and token management
- Optimize retrieval quality with evaluation and reranking
- Partner with IP designers and verification engineers
Perks/Benefits
Skills/Tech-stack
API Development | Agentic AI | Caching | Cloud deployment | ETL | Evaluation | GenAI | Guardrails | Hallucination detection | Hybrid search | Latency monitoring | MCP | Model routing | Observability | Python | Reranking | Retrieval-Augmented Generation | Semantic Search | Token Monitoring | Tracing
Education
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