Director, Applied AI Engineering- Enterprise

Following a record-breaking Q4 2025-our strongest revenue quarter to date, with Enterprise delivering our largest bookings ever-we are accelerating enterprise adoption of frontier data and models through complex, production-grade AI agents.

The Applied AI team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale's proprietary research, data, and infrastructure-unlocking domain expertise through high-quality data and expert feedback.

As Director of Applied AI, you will own the strategy, execution, and growth of a high-impact organization, working directly with some of the world's most sophisticated enterprises to translate generative AI breakthroughs into measurable business outcomes through team building, technical leadership, and deep customer partnerships.

This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.

• Drive enterprise impact with GenAI: Partner directly with customers to identify high-leverage opportunities for generative AI, design solutions, and deliver production systems that create clear business value.
• Lead and scale a GenAI-native Applied AI organization: Build, mentor, and manage multiple teams of Applied AI Engineers and ML Engineers who are native to modern GenAI technologies, agentic systems, and multimodal models.
• Set technical and strategic direction: Define best practices for agent development, evaluation, deployment, and iteration across customer engagements and internal product efforts.
• Bridge frontier research to real-world applications: Translate advances in LLMs, multimodal models, and agentic workflows into practical, scalable solutions across industries.
• Discover model limitations and inspire innovation: Identify failure modes, inefficiencies, and gaps in current models; use these insights to influence internal research, product roadmaps, and customer strategy.
• Partner cross-functionally: Work closely with Product, Research, Sales, and Leadership to shape Applied AI offerings, prioritize investments, and guide long-term platform evolution.
• Influence the broader AI ecosystem: Represent Scale's Applied AI capabilities with customers and partners, and help position Scale as a trusted leader in enterprise GenAI deployment.
  
  

• 8+ years of experience building, deploying, and scaling ML systems in production, including Enterprise-grade Gen AI and agentic applications
• 6+ years of people leadership experience, including managing managers and leading multi-team organizations delivering customer-facing AI products
• Deep applied expertise in Gen AI, including LLM-based systems, agent orchestration, evaluation and reliability frameworks, and production system design
• Experience owning end-to-end AI product delivery-from problem definition and technical architecture to deployment, iteration, and scaling
• Strong technical judgment across software engineering, system design, and applied ML fundamentals
• Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners
• Bachelor's degree required; Master's or PhD in Computer Science or a related field strongly preferred
  
  

• Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments
• Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale
• Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes
  
  

As Director of Applied AI, you will play a critical role in shaping how enterprises adopt, deploy, and trust generative AI at scale. You will build and lead teams that set the standard for applied GenAI and agentic systems, translate frontier capabilities into reliable, production-ready solutions, and deliver measurable business impact for customers. By uncovering model limitations and guiding how AI is applied in real-world environments, you will influence both product direction and the next wave of enterprise AI innovation.

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