Forward Deployed AI Engineering Manager, Enterprise
Lead a team as technical bridge for enterprise customers, architecting and deploying custom AI agents, integrations, and prompt engineering solutions into production environments. Requires 5+ years software engineering with 2+ years management, Python expertise, and cloud experience.
About the job
Key Responsibilities
Customer Integration & Deployment
- Partner with enterprise customers to understand technical infrastructure, data pipelines, and business requirements
- Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
- Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
- Deploy and configure AI models and agents within customer security and compliance boundaries
AI Agent Development
- Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
- Architect multi-agent systems that orchestrate between different models, tools, and data sources
- Implement evaluation frameworks to measure agent performance and iterate toward business objectives
- Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement
Prompt Engineering & Optimization
- Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
- Build and maintain prompt libraries, templates, and best practices for customer use cases
- Conduct systematic prompt experimentation and A/B testing to improve model outputs
- Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate
Leadership & Collaboration
- Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
- Lead a team collaborating with customer data scientists, ML engineers, and software developers
- Work closely with Scale's product and engineering teams to translate customer needs into product improvements
- Document technical architectures, integration patterns, and best practices
Problem Solving & Innovation
- Debug complex technical issues across the entire stack, from data pipelines to model outputs
- Rapidly prototype solutions to unblock customers and prove out new use cases
- Stay current on the latest AI/ML research and tools
- Identify opportunities for productization based on common customer patterns
Required Qualifications
- 5+ years of software engineering experience with 2+ years of management experience and strong fundamentals in data structures, algorithms, and system design
- Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
- Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
- Strong problem-solving skills with the ability to navigate ambiguous requirements
- Excellent communication skills
Preferred Qualifications
Agent Development
- Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
- Experience building and deploying AI agents or autonomous systems in production
- Knowledge of vector databases and semantic search systems
- Contributions to open-source AI/ML projects
Infrastructure
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
- Experience using Terraform, Bicep, or other IaC tools
- Previous work in a devops, platform, or infra role
- Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
Customer Product
- Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
- Domain expertise in verticals like finance, healthcare, government, or manufacturing
- Experience with technical enablement or teaching programs
Skills
Python, LangChain, Llamaindex, Huggingface, OpenAI API, AWS, GCP, Azure, Docker, Kubernetes
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