Frontier Agent Engineering Manager, EnterpriseSan Francisco, CA; New York, NYAbout Scale AIScale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.Role OverviewAs 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.Key ResponsibilitiesCustomer Integration & DeploymentPartner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirementsDesign 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 workflowsDeploy and configure AI models and agents within customer security and compliance boundariesAI Agent DevelopmentDevelop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automationArchitect multi-agent systems that orchestrate between different models, tools, and data sourcesImplement evaluation frameworks to measure agent performance and iterate toward business objectivesDesign human-in-the-loop workflows and feedback mechanisms for continuous agent improvementPrompt Engineering & OptimizationCreate sophisticated prompt engineering strategies optimized for customer-specific domains and dataBuild and maintain prompt libraries, templates, and best practices for customer use casesConduct systematic prompt experimentation and A/B testing to improve model outputsImplement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriateLeadership & CollaborationServe as the Engineering Manager and technical point of contact for strategic enterprise accountsLead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integrationWork closely with Scale's product and engineering teams to translate customer needs into product improvementsDocument technical architectures, integration patterns, and best practicesProblem Solving & InnovationDebug complex technical issues across the entire stack, from data pipelines to model outputsRapidly prototype solutions to unblock customers and prove out new use casesStay current on the latest AI/ML research and tools, bringing innovative approaches to customer problemsIdentify opportunities for productization based on common customer patternsRequired Qualifications5+ years of software engineering experience with 2+ yrs of Management experience with strong fundamentals in data structures, algorithms, and system designProduction 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 infrastructureStrong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutionsExcellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiencesPreferred QualificationsAgent Development WizDeep understanding of LLMs including prompting techniques, embeddings, and RAG architecturesExperience building and deploying AI agents or autonomous systems in productionKnowledge of vector databases and semantic search systemsContributions to open-source AI/ML projectsInfrastructure GuruExperience with containerization (Docker, Kubernetes) and CI/CD pipelinesExperience using Terraform, Bicep, or other Infrastructure as Code (IaC) toolsPrevious work in a devops, platform, or infra roleFamiliarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)Customer Product WhispererProven ability to work with customers in a technical consulting, solutions engineering, or product engineering roleDomain expertise in verticals like finance, healthcare, government, or manufacturingExperience with technical enablement or teaching programsSample ProjectsThe following are some examples of the types of projects we've worked on with customers. All of these projects leverage customer data, integrate directly into customers' existing systems, and are deployed on their infrastructure.Deep Research for Due DiligenceFor a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources.
This solution reliably saves employees hundreds of hours weekly.Churn PredictionWorking with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.Data Extraction Voice AgentWe partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients.
Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.