Tasks:
- * Build and operate LLM applications and services
- * Deploy, evaluate, and monitor production services on AWS and Databricks
- * Develop agentic workflows, RAG systems, and classification pipelines
- * Integrate AI assistants with internal data and systems using MCP servers
- * Pilot AI tools and patterns and lead adoption
Perks/Benefits:
- + 401k
- + Commuter benefits
- + Dental insurance
- + Disability insurance
- + Educational assistance
- + Health and Dependent Care FSA
- + Health savings account
- + Life and AD&D insurance
- + Medical insurance
- + Paid time off
- + Student loan repayment
- + Vision insurance
Skills/Tech stack required:
[Agent Frameworks] [Agentic Workflows] [AI Agent] [AI Agent Frameworks] [AI Evaluation] [Amazon Bedrock] [Anthropic API] [AWS] [CI/CD] [Databricks] [Demand forecasting] [Embeddings] [Generative AI] [Generative AI evaluation] [LLM Engineering] [Machine Learning] [MCP servers] [OpenAI API] [Prompt engineering] [Python] [RAG] [Recommendation Systems] [Software testing] [Vector Databases] [Version control]
Educational requirements:
[Master of Science] [PhD]
Role(s):
[AI Engineer] [AI Solutions Engineer] [Engineer] [Learning Engineer] [Machine Learning Engineer] [Senior AI Solutions Engineer] [Solutions Engineer]