Data Scientist - Machine Learning / Artificial Intelligence

As an AI Assistant Developer at our company, you will be responsible for the following 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. The qualifications required for this role include: - 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. In addition to the required qualifications, the following qualifications are preferred: - 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. As an AI Assistant Developer at our company, you will be responsible for the following 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. The qualifications required for this role include: - 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. In addition to the required qualifications, the following qualifications are preferred: - 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.