Location: Cary, NC
Company: Cadence
**At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.** **Agentic AI Engineer** **Role Summary** Cadence is hiring early-career Agent AI Engineers to join our applied AI team building agentic systems for silicon design. You will work alongside senior AI engineers and chip-design domain experts on the core technical pillars of Cadence's agentic stack: training and adapting models for engineering tasks, engineering high-quality design context (RAG, prompt scaffolds, retrieval pipelines), and tuning the knowledge graphs and vector/graph databases that ground our agents. From day one you will be writing production code that lands in customer-facing AI products and directly accelerates how the world designs chips. **What You Will Do** - Model Development. Train, fine-tune, distill, and evaluate LLMs / SLMs and embedding models for EDA-specific tasks. Hands-on with LoRA / PEFT, instruction tuning, preference optimization (DPO/GRPO), and rigorous eval harnesses for code and reasoning. - Design Context Engineering. Build the retrieval pipelines, prompt scaffolds, and tool-calling specs that feed Cadence agents the right design context (RTL, scripts, logs, reports, methodology docs) at the right token budget. Optimize for accuracy, latency, and cost. - Knowledge Graph & Database Tuning. Design schemas, tune ingestion, and optimize queries for graph DBs (Neo4j, ArangoDB, NebulaGraph) and vector stores (Qdrant, Weaviate, pgvector, Chroma). Keep retrieval fast, accurate, and scoped to the right design hierarchy. - Agent Building Blocks. Implement and harden agent tools, memory, multi-hop reasoning patterns, and guardrails. Triage production failures and iterate. - Data Pipelines. Curate, clean, and label datasets from EDA artifacts (RTL, waveforms, logs, reports, schematics). Build synthetic-data and self-improvement loops where appropriate. - Evaluation & Telemetry. Build offline benchmarks and online metrics. Help defi
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