Director of Engineering, Applied AI
USD 188K-220K Executive-level Full Time
Tasks
- Build agentic AI workflow automation systems
- Build cloud based AI infrastructure for serving
- Build custom RAG and fine tuning solutions
- Co develop AI enabled product features
- Create reusable data pipelines for experimentation
- Design data extraction systems using LLMs
- Drive applied AI technical roadmap
- Ensure observability and model monitoring
- Evaluate and implement AI techniques and frameworks
- Implement AI enabled data accessibility tooling
- Implement responsible AI privacy and ethics standards
- Integrate agentic AI into production systems
- Lead end to end agentic AI application lifecycle
- Manage team leadership and engineering rigor
Perks/Benefits
- N/A
Skills/Tech-stack
AI SDK | AWS SageMaker | Agent systems | Agentic AI | Anthropic | Apache Spark | Autogen | Azure ML | ChromaDB | DBT | Databricks | Embeddings | Google Gemini | Google Vertex | Google Vertex AI | Hugging Face | Hugging Face Transformers | JavaScript | Kafka | Kubeflow | LLM APIs | Langchain | Langgraph | Langsmith | Llamaindex | MLOps | MLflow | Milvus | Multi-Agent | Multi-Agent Systems | Next.js | OpenAI | PGVector | Pinecone | PyTorch | Python | RAG | RLHF | React | SQL | Scikit-learn | Semantic Kernel | Snowflake | TensorFlow | TypeScript | Vector Databases | Vertex AI | Weaviate | Weights and Biases
Education
N/A
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