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Forward Deployed AI Engineering Manager, Enterprise

United States, San Francisco 216000.00 - 270000.00 USD / Year · Job Posted February 20, 2026
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Job Description

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Job Responsibility

  • Partner directly with enterprise customers to understand their 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
  • 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
  • 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
  • Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
  • Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
  • Work closely with Scale's product and engineering teams to translate customer needs into product improvements
  • Document technical architectures, integration patterns, and best practices
  • 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, bringing innovative approaches to customer problems
  • Identify opportunities for productization based on common customer patterns

Requirements

  • 5+ years of software engineering experience
  • 2+ years of Management experience with 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 and rapidly iterate toward solutions
  • Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Nice to have

  • 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
  • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
  • Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
  • Previous work in a devops, platform, or infra role
  • Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
  • 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

What we offer

  • Comprehensive health, dental and vision coverage
  • retirement benefits
  • a learning and development stipend
  • generous PTO
  • equity grant
  • commuter stipend

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