--- title: 'Frontier Agent Engineering Manager, Enterprise at Scale AI' canonical: 'https://feeny.ai/job/frontier-agent-engineering-manager-enterprise-scale-ai-london-hyz2gygke749' type: 'job' last_seen: '2026-10-28' --- # Frontier Agent Engineering Manager, Enterprise at Scale AI - **Company:** Scale AI - **Location:** London, United Kingdom - **Posted:** 2026-10-16 - **Last confirmed live:** 2026-10-28 - **Apply:** https://job-boards.greenhouse.io/scaleai/jobs/4743438005 ## Job description ## About Scale AI Scale 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 Overview 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. ## 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 Required Qualifications - 5+ years of software engineering experience with 3+ 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 ## Preferred Qualifications Agent Development Wiz - 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 Guru - 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) Customer Product Whisperer - 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 Sample Projects The 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 Diligence For 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 Prediction Working 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 Agent We 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. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's [Know Your Rights poster](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our [privacy policy](https://scale.com/legal/privacy) for additional information. ## About Scale AI ## Company Overview - **One-liner**: Scale AI provides high-quality data, RLHF, model evaluations, and full-stack AI infrastructure to help enterprises and governments build, deploy, and oversee reliable AI systems. - **Entity Type**: Private (49% non‑voting stake owned by Meta Platforms as of June 2025; total funding $1.6B across eight rounds) - **Headquarters**: San Francisco, California, United States - **Founded**: 2016 - **Founders**: Alexandr Wang, Lucy Guo (Wang left in June 2025; current CEO is Jason Droege) ## Core Business - **Primary industry**: AI infrastructure, data annotation, large language model (LLM) evaluation, enterprise AI deployment - **Target customers**: B2B – Enterprise and government organizations; also serves leading AI labs (e.g., OpenAI, Google DeepMind, Meta, Microsoft, General Motors) - **Mission**: “Develop reliable AI systems for the world's most important decisions.” ## Products & Services - **Data at Scale**: High-quality training data, annotations, and RLHF for advanced AI models (SaaS + human-in-the-loop service) - **Evaluations**: Rigorous model evaluations, benchmarking, and red‑teaming to measure and improve AI performance (service) - **Applied AI**: Full‑stack AI systems that help enterprises and governments build, deploy, and oversee reliable AI (SaaS + consulting) - **Safety, Evaluation and Alignment Lab**: Research arm focused on LLM alignment and safety (internal R&D; also co‑created the “Humanity's Last Exam” benchmark) - **Subsidiaries**: Remotasks (computer vision and autonomous vehicle data labeling), Outlier (LLM data annotation) ## Market Standing - **Valuation**: $29B (as of 2025 – cited on scale.com) - **Key Metric**: Total Funding – $1.6B (including the $14B Meta investment that acquired a 49% non‑voting stake in June 2025) - **Notable Investors/Partners**: Meta Platforms (49% owner), with commercial customers including Google, Microsoft, Meta, General Motors, OpenAI, and Time. Also works with U.S. and Qatari governments. - **Growth Signals**: - Headcount: Scale.com cites “1,000+” employees; LinkedIn reports 3,751 employees (+32.1% YoY). - 90% of the world’s leading generative AI model builders are powered by Scale. - 15 billion human decisions used to train AI models; $1 billion paid to contributors globally. - Active job postings: 284+ (as of July 2025), with strong hiring in enterprise engineering, AI agents, and solutions roles. ## Competitive Advantages - **Data moat**: Scale’s proprietary Data Engine and access to millions of human‑annotated decisions create high‑quality training data that competitors cannot easily replicate. - **Trust & adoption**: Used by 90% of leading GenAI builders; runs private benchmarks for the most ambitious AI companies. - **Government credibility**: Direct contracts with the U.S. Department of Defense and international governments (e.g., Qatar) – a high‑barrier entry point. - **Full‑stack offering**: From raw data annotation to LLM evaluation and end‑to‑end applied AI deployment, Scale covers the entire AI lifecycle. - **Research leadership**: In‑house Safety, Evaluation and Alignment Lab; co‑creator of the “Humanity's Last Exam” benchmark. ## Strategic Focus - **Enterprise GenAI agents**: Ramping up “AgentOps” and “Frontier Agents” engineering teams (many open roles in SF, NY, London, Budapest). - **Healthcare & life sciences**: Hiring dedicated GTM leaders and AI strategists for healthcare vertical. - **International expansion**: Growing offices in London, Budapest, Mexico City, and Washington DC. - **Safety and alignment**: Continued investment in red‑teaming, model evaluations, and government‑focused AI safety contracts. ## Why Work Here - **Mission‑driven**: “Develop reliable AI systems for the world’s most important decisions” – directly shaping frontier AI capabilities. - **Compensation & benefits**: Comprehensive health, dental, vision, mental health services; generous PTO; annual learning & development stipend; parental leave; ERGs; guest‑friendly offices with happy hours, game nights, book clubs. - **Engineering culture**: Credos such as “Write the Market,” “Find the 20%,” “Earn Customer Love,” and “Quality is Our Cheat Code” emphasize impact over effort, customer obsession, and structured thinking. - **Growth trajectory**: Rapid headcount growth (+32%), major Meta investment, and expansion into new verticals signal a company in high‑growth mode. - **Flexible work**: Offices in SF, NY, London, Budapest, Mexico City, DC; the careers page highlights “flexible environment,” though specific remote/hybrid policy is not explicitly stated. ## Sources 1. [scale.com](https://scale.com/about) 2. [scale.com](https://scale.com/) 3. [scale.com/careers](https://scale.com/careers) 4. [linkedin.com](https://www.linkedin.com/company/scaleai) 5. [greenhouse.io](https://job-boards.greenhouse.io/scaleai) ## Other roles at Scale AI - [Global Procurement Analyst](https://feeny.ai/job/global-procurement-analyst-scale-ai-mexico-city-5ncmbbf10tyr) — Mexico City, Mexico - [Frontier Agent Engineering Manager, Enterprise](https://feeny.ai/job/frontier-agent-engineering-manager-enterprise-scale-ai-new-york-vdv41n0x0k7a) — New York, NY - [Creative Advisor - Human Frontier Collective](https://feeny.ai/job/creative-advisor-human-frontier-collective-scale-ai-united-states-2qypenvct6st) — United States - [Infrastructure Software Engineer, Apps Platform](https://feeny.ai/job/infrastructure-software-engineer-apps-platform-scale-ai-london-9c3h5bndc096) — London, United Kingdom - [Contracts Manager](https://feeny.ai/job/contracts-manager-scale-ai-washington-5nk1xgw7a4q4) — Washington, DC - [Machine Learning Research Intern (Summer 2027)](https://feeny.ai/job/machine-learning-research-intern-summer-2027-scale-ai-new-york-zwkg8x2mh49n) — New York, NY / San Francisco, CA - [Web Designer, Brand Web Experience](https://feeny.ai/job/web-designer-brand-web-experience-scale-ai-san-francisco-0y4xvdt1v4qq) — San Francisco, CA - [Head of Strategic Partnerships, Global Systems Integrators](https://feeny.ai/job/head-of-strategic-partnerships-global-systems-integrators-scale-ai-san-francisco-a9spswq58jhk) — San Francisco, CA - [Head of Strategic Partnerships, Labs](https://feeny.ai/job/head-of-strategic-partnerships-labs-scale-ai-san-francisco-vye4n623xfpv) — San Francisco, CA - [Engagement Manager, Public Sector (Miami, FL)](https://feeny.ai/job/engagement-manager-public-sector-miami-fl-scale-ai-miami-3ndjz5cd9kra) — Miami, FL