Director of Engineering - PinAI

DoubleVerify • New York, NY

18d • $118,000 - $235,000 • Hybrid

About The Position

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)

Requirements

• 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
• Agentic AI & LLM Frameworks: Deep expertise in building agentic systems using frameworks like LangChain, LangGraph, AutoGPT, or similar agent architectures
• Model Context Protocol (MCP): Experience with MCP or similar protocols for building modular AI agent components and tool integrations
• Conversational AI: Strong background in designing and implementing conversational AI systems, dialogue management, and natural language understanding
• Evaluation Frameworks: Expertise in building comprehensive evaluation (evals) systems for LLM applications, including accuracy metrics, hallucination detection, and human-in-the-loop feedback
• LLM Technologies: Hands-on experience with major LLM providers (OpenAI, Anthropic, Google, etc.) and open-source models
• Backend Engineering: Proficiency in Python, Java, Scala, or similar languages for building scalable backend systems
• Cloud & Infrastructure: Experience with cloud platforms (GCP, AWS, Azure) and containerization (Kubernetes, Docker)
• Exceptional ability to architect complex systems while adhering to engineering best practices
• Strong technical communication skills; ability to explain AI concepts to non-technical stakeholders
• Experience building and scaling high-performing, diverse engineering teams
• Proven track record of delivering ambitious projects on time with cross-functional teams
• Strategic thinker with the ability to balance innovation with practical execution
• Strong stakeholder management and influencing skills
• BS/MS in Computer Science, Machine Learning, AI, or related technical field (PhD preferred)

Nice To Haves

• Experience with Prompt Engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques
• Familiarity with agent evaluation tools like DeepEval, LangSmith, Weights & Biases, or custom eval frameworks
• Knowledge of responsible AI practices, bias mitigation, and AI safety
• Experience in AdTech, Analytics, or Business Intelligence domains
• Contributions to open-source AI projects or published research in AI/ML
• Experience with modern frontend frameworks (React, Angular) for AI interfaces
• Familiarity with Looker, Snowflake, or similar analytics platforms
• Track record of innovation and patents in AI/ML space

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

Benefits

• Opportunity to lead a cutting-edge AI initiative at a publicly-traded, industry-leading company
• Work with Fortune 500 clients on transformative AI solutions
• Collaborative, innovative culture with a focus on continuous learning
• Competitive compensation including base salary, bonus, and equity
• Comprehensive benefits package
• Professional development and conference opportunities
• Hybrid work flexibility

What This Job Offers

• Job Type: Full-time
• Career Level: Director