Key Responsibilities:
- Develop and deploy Slack-based AI assistants powered by Gemini models
- Design and implement prompt templates tailored to enterprise data platforms such as Looker and Confluence
- Establish and manage an embedding pipeline for Confluence documentation
- Build and maintain orchestration logic for executing prompts and retrieving relevant data
- Set up secure API authentication and implement role-based access controls for integrated systems
- Connect to and validate vector store operations using Pinecone, Weaviate, or Snowflake vector extensions
- Contribute to internal documentation, walkthrough sessions, and user acceptance test (UAT) planning
- Participate in Agile ceremonies including daily standups, sprint planning, demos, and retrospectives
Required Qualifications:
- Proven hands-on experience deploying Gemini or similar large language models in production environments
- Proficiency in Python and experience with orchestration tools and prompt engineering practices
- Familiarity with vector databases and embedding workflows
- Experience integrating APIs for enterprise data tools such as Looker and Confluence
- Strong understanding of access control frameworks and enterprise authentication protocols
- Track record of working effectively in Agile, sprint-based development environments
Preferred Qualifications:
- Experience with Slack app development and deployment workflows
- Background in MLOps, LLMOps, or orchestration of large-scale AI systems
- Excellent written and verbal communication skills and ability to collaborate in cross-functional teams
