Senior Manager, AI Engineering

🕒 Setembro 24

🌵 Arizona, California, +9 estados a mais – Remoto

🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🍂 Massachusetts – Remote ❄️ Minnesota – Remote 🔔 Pennsylvania – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ☕ Washington – Remote

💵 $137.500 - $185.600 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 1%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Deckers Brands

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1973

🏭 Manufatura

📦 Logística

👗 Moda

Manufacturing • Logistics • Fashion

Deckers Brands é uma empresa global de calçados e vestuário, conhecida por seus produtos inovadores em várias marcas populares. A empresa projeta, comercializa e distribui seus produtos mundialmente, com forte ênfase na qualidade e desempenho. Deckers Brands é reconhecida por seu compromisso com a sustentabilidade e por criar produtos que são moda e funcionais.

Descrição

• Own the enterprise AI platform, including governed access to foundation models, unified gateway, model routing, prompt and context management, and cost controls • Define and maintain reusable AI engineering patterns for retrieval augmented generation, agents, orchestration, and LLM application architecture • Lead the evaluation framework for AI systems, including offline evaluation suites, online quality monitoring, regression testing, and release acceptance criteria • Deliver AI applications into production across customer-facing and internal use cases • Manage operational quality for production AI systems, including latency, availability, cost per interaction, quality regression detection, and support coverage • Track the foundation model and AI tooling landscape and manage migrations as models and providers change • Own the AI engineering roadmap and staffing plan • Manage and mentor AI engineers and direct external AI delivery partners • Establish production-readiness standards, including guardrails, safety controls, human-in-the-loop design, fallback behavior, and incident response • Implement responsible AI policy as engineering controls, including model risk documentation, evaluation evidence, output monitoring, and audit trails • Partner with business, digital, data, ML engineering, enterprise architecture, security, privacy, and infrastructure teams to prioritize AI use cases

🎯 Requisitos

• Bachelor’s degree required, preferably in Computer Science, Engineering, or a related technical field • 8–12 years of software, data, or machine learning engineering experience building production systems • 3–5+ years leading engineering teams in cloud-native environments • 3+ years delivering production AI or machine learning systems • 2+ years building generative AI or large language model applications • Experience taking generative AI from proof of concept into governed production, including evaluation, guardrails, and monitoring • Hands-on experience with retrieval augmented generation, agent frameworks, tool use, and orchestration patterns • Experience with foundation model platforms such as AWS Bedrock, Azure OpenAI, or equivalent • Deep understanding of large language model application architecture • Strong grasp of AI evaluation methods, safety and security concerns, and cost awareness for AI systems • Strong leadership and people-management skills • Excellent problem-solving, analytical thinking, and decision-making skills • Strong communication and influencing skills across technical and business stakeholders • Comfortable working in a fast-paced, matrixed, and global environment

🏖️ Benefícios

• Competitive pay and bonuses • Financial planning and wellbeing programs • Time away from work • Employee discounts • Community-based programs • Personal and professional development opportunities • Health and wellness programs