Sr Generative AI Engineer (Agentic AI & RAG)
Tasks
- Build patient services AI workflows
- Build reusable agent architectures and patterns
- Create MuleSoft DataWeave integrations
- Create Salesforce Health Cloud integrations
- Create reusable prompt templates
- Design develop production AI agents
- Develop maintain RAG pipelines
- Establish evaluation harnesses and quality standards
- Implement MCP Server integrations
- Integrate AI into Java based systems
- Monitor production agents accuracy latency cost performance drift
- Own agent lifecycle deployment testing evaluation monitoring optimization retirement
- Review AI generated code for quality and compliance
Perks/Benefits
- Continuous learning
- Follow the sun collaboration
- Healthcare mission impact
- Inclusive culture
- Professional development
Skills/Tech-stack
AI Agent Builder | AI platforms | Agent Builder | Agent Orchestration | Apex | BigQuery | Claude | Cloud AI | Cloud AI Platforms | CrewAI | DataWeave | Development Lifecycle | Embeddings | Evaluation | Gemini | Gemini Enterprise | GraphQL | Health Cloud | Java | JavaScript | LWC | Langchain | Langgraph | Language Models | Large Language Models | Lightning Web | Lightning Web Components | MCP | Model Context Protocol | MuleSoft | OpenAI | PostgreSQL | Prompt engineering | Python | RAG | REST APIs | Retrieval architecture | Retrieval workflows | Salesforce Health Cloud | Software Development Lifecycle | Software development | TypeScript | Vector Databases | Vector Stores | Vertex AI | Vertex AI Agent Builder | Web Components
Education
N/A
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