Frontier Agent Engineering Manager, Enterprise

Scale AI
San Francisco, New York
Workplace: OnsiteFull timeUSD 216,000 - 270,000 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Communication","Leadership","Problem-solving","Team leadership"]

Lead a team to architect and deploy enterprise AI solutions for strategic customers, bridging Scale AI’s capabilities with customer workflows. You’ll manage technically, guide integration, and drive production-ready AI agents, prompt strategies, and collaboration with product and customer teams to deliver scaled, repeatable outcomes.

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FursaFursa
Scale AI
Scale AI
7 months ago

Frontier Agent Engineering Manager, Enterprise

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Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Lead a team to architect and deploy enterprise AI solutions for strategic customers, bridging Scale AI’s capabilities with customer workflows. You’ll manage technically, guide integration, and drive production-ready AI agents, prompt strategies, and collaboration with product and customer teams to deliver scaled, repeatable outcomes.
Location: San Francisco, New York
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Manager level

Key Responsibilities

  • •Customer Integration & Deployment: 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
  • •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 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
  • •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, bringing innovative approaches to customer problems; Identify opportunities for productization based on common customer patterns

Pay and Benefits

Salary: USD 216,000 - 270,000 annually
Perks:Health InsuranceDentalVisionRetirement BenefitsLearning StipendPaid Leave

Key Requirements

  • •5+ years of software engineering experience with 2+ yrs 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
Experience:5+ yearsEnterprise AIArtificial intelligence
Skills:CommunicationLeadershipProblem-solvingTeam leadership
Languages:English
Tech Stack:PythonLangChainLlamaIndexHuggingFaceOpenAI APIAWSGCPAzureDockerKubernetesTerraformData warehousesETLData pipelinesAI agents

Company Brief

Scale AI
Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2016
WebsiteLinkedIn