Director - AI Research and Engineering Efficiency (Circuit Platform)
Tasks
- Benchmark emerging LLM and agent harnesses
- Build model evaluation harnesses
- Build reusable evaluation frameworks and deployment pipelines
- Define agentic system architecture
- Direct AI research and engineering team
- Drive model serving efficiency optimizations
- Establish offline and online metrics
- Establish technical standards for secure observable auditable agents
- Lead architecture and code reviews
- Lead fine tuning for security and quality
- Manage enterprise LLM and agent platform scale
- Optimize model spend portfolio and reliability targets
- Own frontier and open weight LLM strategy
- Translate AI research into production capabilities
Perks/Benefits
Skills/Tech-stack
AI Governance | Agentic Systems | Artificial Intelligence | Batching | Caching | Context Optimization | Distillation | Distributed Platform | Distributed Systems | Distributed platform design | Enterprise AI | Enterprise AI governance | Fine Tuning | Human-in-the-loop | Kubernetes | Language Models | Large Language Models | LoRA | Machine Learning | Model Compression | Model Evaluation | Model Serving | Model routing | Observability | Orchestration | Platform Design | Policy enforcement | Production software | Production software engineering | Prompt engineering | QLoRA | Quantization | Ray | Retrieval-Augmented Generation | Software Engineering | Structured outputs | TensorRT-LLM | The Loop | Tool-Calling | VLLM
Education
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