--- title: 'Frontier Agents Engineer (Applied AI) at Scale AI' canonical: 'https://feeny.ai/job/frontier-agents-engineer-applied-ai-scale-ai-san-francisco-jamevdq6gsnw' type: 'job' last_seen: '2026-09-09' --- # Frontier Agents Engineer (Applied AI) at Scale AI - **Company:** Scale AI - **Location:** San Francisco, CA / New York, NY - **Compensation:** $180k–$225k - **Posted:** 2026-07-31 - **Last confirmed live:** 2026-09-09 - **Apply:** https://job-boards.greenhouse.io/scaleai/jobs/4720573005 ## 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 the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI), you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. ## What You'll Build Frontier AI Systems - Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. - Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows. - Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data. - Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight. - Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures. Experimentation & Evaluation - Own the full experimentation lifecycle, from hypothesis generation to production rollout. - Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation. - Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures. - Continuously evaluate newly released frontier models and determine where they meaningfully improve quality, latency, reliability, or cost. - Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback. - Measure success through business outcomes, not benchmark scores. Production AI Engineering - Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost. - Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines that enable safe deployment in high-stakes environments. - Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments. - Build human-in-the-loop workflows that effectively combine AI automation with expert oversight. Customer Innovation - Partner directly with enterprise customers to understand their business, data, and operational challenges. - Translate ambiguous customer problems into production AI architectures. - Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems. - Identify reusable patterns that become core capabilities across many enterprise deployments. What Makes This Role Different You'll work across the full lifecycle of modern AI systems: - Designing reasoning and agent architectures - Building retrieval, memory, and customer intelligence systems - Developing predictive models that work alongside LLMs - Running experiments and ablation studies - Shipping production systems into enterprise environments - Measuring business impact through online experimentation - Continuously improving agents using real-world feedback We believe the fastest way to grow as an Frontier Agents engineer is to solve many different AI problems, not the same problem repeatedly. You'll work across diverse industries, datasets, model architectures, and agentic systems, rapidly developing intuition for what makes AI systems successful in production. Required Qualifications - 4+ years of software engineering, machine learning, or applied AI experience. - Strong Python programming skills. - Experience building production AI systems using LLMs. - Experience with modern AI tooling, including OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems. - Strong understanding of machine learning fundamentals and modern language models. - Experience designing or evaluating AI systems using quantitative metrics. - Excellent communication skills and the ability to work directly with enterprise customers. ## Preferred Qualifications Applied AI - Experience building production AI agents or autonomous systems. - Deep understanding of reasoning, retrieval, memory, planning, and tool use. - Experience designing evaluation frameworks for LLMs and agentic systems. - Experience with RAG, semantic search, knowledge graphs, customer intelligence systems, or structured knowledge representations. - Experience with fine-tuning, distillation, reinforcement learning, small language models, or model optimization. - Familiarity with multimodal AI systems and frontier foundation models. Software Engineering - Experience building distributed production systems. - Experience with cloud platforms such as AWS, Azure, or GCP. - Experience with Docker, Kubernetes, CI/CD, and production observability. - Experience integrating AI systems into enterprise software environments. Customer Engineering - Experience working directly with enterprise customers. - Ability to translate ambiguous business problems into technical architectures. - Strong written and verbal communication skills. - Experience leading technical workshops, architecture reviews, or customer design sessions. Dual Fluency While this role initially emphasizes Applied AI and machine learning, every Frontier Agent Engineer develops expertise across both Applied AI and Forward Deployed Engineering. Over time, you'll gain hands-on experience integrating AI systems into enterprise environments, deploying production infrastructure, and working directly with customer engineering teams. Our goal is to develop engineers who can move seamlessly between cutting-edge AI research and real-world production systems. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $180,000—$225,000 USD 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. 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