
AI Engineer
5 days ago
This role involves working with cutting-edge generative AI models to integrate them seamlessly into enterprise software.
- Generative AI & LLM Integration: The primary responsibility is to develop, deploy and fine-tune large language models (LLMs) within a production environment.
- AI Orchestration & MLOps: Building the infrastructure that enables the AI to function efficiently includes managing orchestration logic, setting up embedding pipelines, and ensuring data retrieval and processing occur smoothly.
- Vector Databases & Data Engineering: Proficiency in vector databases (such as Pinecone or Weaviate) and creating embeddings from structured and unstructured data are essential for enabling the AI to retrieve relevant information.
- API & System Integration: Strong technical skills are required to connect various platforms, set up API authentication, and implement role-based access controls to ensure secure data access.
- Agile Development: Familiarity with Agile methodologies, including daily standups, sprint demos, and user acceptance testing, is necessary for managing projects and meeting deadlines.
Key Responsibilities:
- Integrate Gemini models into corporate platforms like Slack and Confluence.
- Build infrastructure that makes the AI work, including managing orchestration logic and setting up embedding pipelines.
- Work with vector databases to create embeddings from structured and unstructured data.
- Develop strong technical skills to connect various platforms and ensure secure data access.
We Offer:
- Opportunities to work on cutting-edge AI technology.
- Collaborative and dynamic work environment.
- Continuous learning and growth opportunities.
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