- Develop and deploy AI-powered Slack assistants using Gemini large language models.
- Design prompt templates tailored to enterprise use cases, specifically for Looker and Confluence data.
- Implement and manage an embedding pipeline for Confluence documentation to enable semantic search and contextual relevance.
- Build orchestration logic for managing prompt execution, API interaction, and contextual data retrieval.
- Set up secure API authentication protocols and implement role-based access control across integrated systems.
- Integrate and validate vector store operations using platforms such as Pinecone, Weaviate, or Snowflake vector extension.
- Collaborate with cross-functional teams and participate in Agile ceremonies, including daily standups and sprint demos.
- Contribute to technical documentation, internal walkthroughs, and user acceptance testing planning.
Required Qualifications:
- Hands-on experience deploying Gemini or other large language models in production environments.
- Strong proficiency in Python, orchestration tools, and prompt engineering techniques.
- Experience working with vector databases and embedding workflows.
- Proficient in integrating APIs with enterprise platforms like Looker and Confluence.
- Strong understanding of access control frameworks and enterprise-grade authentication mechanisms.
- Proven track record of working in Agile, sprint-based software development environments.
Preferred Qualifications:
- Experience in Slack app development, including deployment and user interaction flows.
- Background in MLOps, LLMOps, or large-scale AI orchestration.
- Strong communication skills and ability to work effectively within cross-functional teams.
