About the job
About Scale AI
Scale AI serves as the foundational data platform for artificial intelligence, empowering organizations to develop and implement robust production AI applications. We collaborate with prominent enterprises and government entities to expedite their AI projects through our advanced data annotation platform, generative AI solutions, and enterprise-grade AI capabilities.
Role Overview
We are seeking a Forward Deployed AI Engineering Manager for our Enterprise team. In this pivotal role, you will act as the technical liaison between Scale AI's state-of-the-art AI solutions and our key clients. You will engage with enterprise customers to identify their specific challenges, lead a team focused on designing custom AI solutions, and oversee the successful deployment and integration of AI systems in production settings.
This managerial position merges extensive engineering and AI expertise with direct involvement in customer-centric challenges. You will collaborate directly with client engineering teams to embed AI into their essential workflows.
Key Responsibilities
Customer Integration & Deployment
- Engage directly with enterprise customers to comprehend their technical infrastructure, data pipelines, and business needs.
- Design and execute custom integrations between Scale AI's platform and client data environments, including cloud platforms, data warehouses, and internal APIs.
- Create robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows.
- Deploy and configure AI models and agents within the client's security and compliance frameworks.
AI Agent Development
- Develop production-ready AI agents tailored to customer use cases across various domains, such as customer support, data analysis, content generation, and workflow automation.
- Design architecture for multi-agent systems that manage interactions between different models, tools, and data sources.
- Implement evaluation frameworks to assess agent performance and refine strategies to achieve business objectives.
- Create human-in-the-loop processes and feedback mechanisms to facilitate continuous improvements of the agents.
Prompt Engineering & Optimization
- Develop sophisticated prompt engineering strategies tailored to customer-specific domains and data.
- Establish and maintain prompt libraries, templates, and best practices for customer applications.
- Conduct systematic prompt experimentation and A/B testing to enhance model outputs.
- Implement Retrieval-Augmented Generation (RAG) techniques to optimize AI performance.

