Director of Engineering - PinAI

About the role

DoubleVerify is the leading independent provider of marketing measurement software, data and analytics that authenticates the quality and effectiveness of digital media for the world's largest brands and media platforms. DV provides media transparency and accountability to deliver the highest level of impression quality for maximum advertising performance. Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best in class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com. Role Overview We are seeking an exceptional Director of Engineering to lead our PinAI team, DoubleVerify's strategic initiative in conversational AI and agentic systems. In this role, you will spearhead the development of an AI-powered conversational interface for Pinnacle, transforming how our Fortune 500 clients interact with and derive insights from their advertising data. The PinAI platform leverages cutting-edge AI technologies including agentic AI architectures, Model Context Protocol (MCP), and advanced LLM capabilities to deliver intelligent, context-aware analytics through natural language interactions. This role is ideal for a visionary technical leader who is passionate about AI innovation, has deep experience in conversational AI systems, and possesses exceptional architectural, engineering, and people leadership skills. Location: New York, NY (Hybrid)

Responsibilities

• Strategic Leadership & Vision
• Define and execute the technical vision and roadmap for PinAI/Pin Chat, aligning AI initiatives with DoubleVerify's strategic objectives
• Lead the design and architecture of agentic AI systems that leverage Model Context Protocol (MCP) for scalable, extensible AI agent frameworks
• Drive innovation in conversational AI experiences that transform complex analytics into intuitive, natural language interactions
• Establish technical standards for AI/ML engineering, including evaluation frameworks, prompt engineering, and model performance optimization
• Partner with Product, Data Science, and Architecture teams to translate business requirements into scalable AI solutions
• Team Leadership & Development
• Build, mentor, and scale a world-class team of AI/ML engineers, software engineers, and technical leads
• Attract top-tier talent with expertise in LLMs, agent architectures, conversational AI, and distributed systems
• Foster a culture of innovation, experimentation, and continuous learning in AI technologies
• Provide hands-on technical guidance through architecture reviews, design discussions, and code reviews
• Develop career paths and growth opportunities for team members across AI and engineering disciplines
• Technical Excellence & Delivery
• Oversee the development of agentic AI systems using frameworks like LangChain, LangGraph, and custom agent architectures
• Implement robust evaluation (evals) frameworks to measure and improve AI agent performance, accuracy, and user satisfaction
• Design and build conversational AI interfaces that understand context, maintain conversation history, and provide intelligent responses
• Architect solutions leveraging MCP (Model Context Protocol) to create modular, reusable AI components and tools
• Integrate with Pinnacle's existing analytics infrastructure including Looker, data APIs, and authentication systems
• Ensure production-grade quality through comprehensive testing, monitoring, observability, and reliability engineering
• Cross-Functional Collaboration
• Collaborate with Product Management to define AI-powered features and user experiences
• Partner with Data Science teams on model selection, fine-tuning, and prompt optimization strategies
• Work with Platform Engineering to ensure scalable infrastructure for LLM deployments and agent orchestration
• Engage with Security and Compliance teams to implement responsible AI practices and data governance
• Coordinate with UX/UI teams to create seamless conversational interfaces
• Operational Excellence
• Define and track KPIs for AI system performance, including response accuracy, latency, user satisfaction, and engagement metrics
• Implement MLOps best practices for model deployment, versioning, monitoring, and continuous improvement
• Optimize costs associated with LLM API usage and infrastructure while maintaining quality
• Establish incident response protocols and SLAs for AI-powered features
• Drive continuous improvement through retrospectives, evals analysis, and user feedback loops

Requirements

• Required Qualifications
• 10+ years of software engineering experience building production systems at scale
• 5+ years in engineering leadership roles, managing teams of 5-15+ engineers
• Hands-on experience with AI/ML systems, particularly LLMs and conversational AI
• Proven track record of delivering AI-powered products from concept to production
• Technical Expertise:
• Agentic AI

Benefits

Additional Information

Director of Engineering - PinAI

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