Key Responsibilities:
- AI Assistant Development
- Develop and deploy Slack-based AI assistants leveraging Gemini models tailored for enterprise workflows.
- Prompt Engineering
- Design and implement optimized prompt templates for enterprise data use cases, including integrations with Looker and Confluence.
- Embedding Pipeline Management
- Establish and maintain a scalable embedding pipeline for Confluence documentation.
- Orchestration Logic
- Build and maintain orchestration logic for prompt execution and contextual data retrieval.
- Authentication & Access Control
- Configure API authentication and enforce role-based access controls for integrated systems.
- Vector Store Integration
- Connect and validate operations with vector databases such as Pinecone, Weaviate, or Snowflake vector extension.
- Documentation & Testing
- Contribute to internal documentation, conduct walkthroughs, and assist in user acceptance testing (UAT) planning.
- Agile Collaboration
- Participate in Agile ceremonies including daily standups, sprint planning, and demos.
Required Qualifications:
- Proven experience deploying Gemini or other large language models (LLMs) in production environments
- Proficiency in Python, orchestration tools, and advanced prompt engineering
- Strong knowledge of embedding workflows and vector databases
- Experience integrating APIs with enterprise platforms like Looker and Confluence
- Understanding of enterprise authentication protocols and role-based access control
- Background working in Agile, sprint-based environments
Preferred Qualifications:
- Hands-on experience with Slack app development and deployment
- Familiarity with MLOps, LLMOps, or orchestration of large-scale AI systems
- Excellent communication skills and ability to collaborate with cross-functional teams
