Director of AI Engineering
United States - Remote
R
USD 195K-260K (estimate) Executive-level Full Time
Tasks
- Architect production AI ML systems
- Build and maintain evals frameworks
- Close feedback loops on model quality
- Communicate AI capabilities and limitations
- Define quality bars for agentic workflows
- Design RAG pipelines
- Design agent loop with planning memory tools and error recovery
- Design production observability with tracing cost latency
- Drive agentic coding tool adoption
- Hire and develop engineers
- Manage ML lifecycle experimentation deployment monitoring iteration
- Manage distributed data and ML team
- Measure PR throughput
- Optimize LLM inference and serving
- Oversee training data collection curation labeling
- Own AI roadmap
- Own model performance metrics
- Partner on infrastructure data pipelines APIs
- Partner with product on roadmap and trade offs
- Set model quality evaluation standards
Perks/Benefits
- 401k match
- Annual company retreats
- Medical, dental, vision benefits
- Paid time off
- Promote from within
- Remote work
Skills/Tech-stack
A/B | A/B Testing | API Design | AWS | Agent Orchestration | Agent systems | Agentic Workflows | Anthropic SDK | Asynchronous programming | B testing | Celery | Distributed Systems | Evals Frameworks | Fine Tuning | Function Calling | Inference Optimization | Instruction Tuning | LLM Inference | LLM Inference Optimization | Language Models | Large Language Models | LoRA | Machine Learning | Model Fine-tuning | Model Serving | Multi-Agent | Multi-Agent Systems | Multi-agent orchestration | Observability | OpenAI SDK | PostgreSQL | Python | Q LoRA | RAG | REST | Retrieval-Augmented Generation | TGI | Text Generation | Text generation inference | Tracing | VLLM
Education
N/A
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