Frontier Agent Engineering Manager, Enterprise

Scale AI • New York, NY

1d • $227,000 - $325,000

About The Position

As a Forward Deployed AI Engineering Manager on Scale AI’s Enterprise team, this role serves as the technical bridge between Scale AI’s AI capabilities and strategic enterprise customers. The manager works with customers to understand their technical challenges, leads a team that architects and deploys tailored AI solutions, and supports successful adoption of AI systems in production. The position combines engineering and AI expertise, team leadership, and customer-facing work, including partnering directly with customer engineering teams to integrate AI into critical workflows.

The role covers customer integration and deployment, production AI agent development, prompt engineering and optimization, and technical leadership. It includes designing customer-specific integrations, data connectors and ETL pipelines; deploying AI models and agents within customer security and compliance boundaries; building multi-agent systems, evaluation frameworks, and human-in-the-loop workflows; and developing RAG systems and fine-tuning pipelines where appropriate. The manager also serves as the technical point of contact for strategic accounts, collaborates with customer and Scale teams, documents architectures and practices, debugs issues across the stack, prototypes solutions, and identifies opportunities to productize recurring customer needs.

Projects may include deep research agents, churn prediction and next-best-action systems, and voice agents for health information gathering. Customer solutions use customer data, integrate with existing systems, and are deployed on customer infrastructure.

Compensation for eligible roles includes base salary, equity, and benefits. The stated base salary range for this full-time position in San Francisco and New York is $227,000–$325,000 USD. Final compensation depends on factors including work location, skills, experience, qualifications, interview performance, and education or training. Benefits include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, generous PTO, and potentially a commuter stipend. Candidates must wait 90 days before being reconsidered for the same role.

Requirements

• At least 5 years of software engineering experience.
• At least 3 years of management experience.
• Strong fundamentals in data structures, algorithms, and system design.
• Production Python expertise and experience with modern ML/AI frameworks such as LangChain, LlamaIndex, Hugging Face, or the OpenAI API.
• Experience with cloud platforms such as AWS, GCP, or Azure and modern data infrastructure.
• Strong problem-solving skills, including the ability to navigate ambiguous requirements and iterate rapidly toward solutions.
• Excellent communication skills and the ability to explain complex technical concepts to technical and non-technical audiences.

Nice To Haves

• 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 technologies such as Docker and Kubernetes, and CI/CD pipelines.
• Experience using Terraform, Bicep, or other Infrastructure as Code tools.
• Previous work in a DevOps, platform, or infrastructure role.
• Familiarity with enterprise security, compliance, and governance requirements such as SOC 2, GDPR, or HIPAA.
• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role.
• Domain expertise in finance, healthcare, government, or manufacturing.
• Experience with technical enablement or teaching programs.

Responsibilities

• Partner 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, including cloud platforms, data warehouses, and internal APIs.
• Build 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 for customer use cases such as customer support, data analysis, content generation, and workflow automation.
• Architect multi-agent systems that coordinate models, tools, and data sources.
• Implement evaluation frameworks to measure agent performance and improve it against business objectives.
• Design human-in-the-loop workflows and feedback mechanisms for ongoing agent improvement.
• Create customer-specific prompt engineering strategies, libraries, templates, and best practices.
• Conduct prompt experimentation and A/B testing to improve model outputs.
• Implement RAG systems and fine-tuning pipelines where appropriate.
• Serve as Engineering Manager and technical point of contact for strategic enterprise accounts.
• Lead a team collaborating with customer data scientists, ML engineers, and software developers to support smooth integration.
• Work with Scale product and engineering teams to translate customer needs into product improvements.
• Document technical architectures, integration patterns, and best practices.
• Debug technical issues across the stack, from data pipelines to model outputs.
• Rapidly prototype solutions to unblock customers and validate use cases.
• Stay current on AI/ML research and tools and apply relevant approaches to customer problems.
• Identify opportunities to productize solutions based on common customer patterns.

Benefits

• Comprehensive health coverage
• Dental coverage
• Vision coverage
• Retirement benefits
• Learning and development stipend
• Generous PTO
• Potential commuter stipend
• Equity-based compensation for eligible roles, subject to Board of Director approval

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed