VP Engineering

The Role

As the VP of Engineering, you will be a key technical leader responsible for implementing engineering frameworks, processes, and AI-driven solutions that enable our performance products to scale globally. Reporting to the Head of Engineering, you will combine hands-on technical expertise with strategic thinking to architect and build cutting-edge AI-powered advertising solutions. This role requires deep proficiency in AI/ML technologies, modern software engineering practices, and the ability to translate complex technical requirements into scalable, production-ready systems. You will be instrumental in establishing coding standards, CI/CD pipelines, and engineering best practices while actively contributing to the codebase alongside your team. The ideal candidate is equally comfortable architecting AI agent systems as they are debugging production issues or reviewing pull requests. You thrive in fast-paced environments, stay current with emerging AI technologies, and are passionate about building systems that deliver measurable business impact across digital touchpoints.

Responsibilities

• Lead by example through active contribution to the codebase, including designing and implementing core AI/ML features and infrastructure components.
• Architect and develop AI agent systems, LLM integrations, and machine learning pipelines that power our performance advertising products.
• Conduct code reviews, establish coding standards, and mentor team members on AI/ML best practices and software engineering principles.
• Design and implement APIs, data pipelines, and microservices that integrate with platforms including Google, Meta, Amazon, and programmatic advertising systems.
• Define and implement engineering frameworks that enable rapid development and deployment of AI-powered features at scale.
• Establish CI/CD pipelines, automated testing strategies, and deployment processes that ensure reliability and velocity.
• Drive adoption of DevOps and MLOps best practices, including model versioning, monitoring, and continuous improvement workflows.
• Create technical documentation, architecture decision records, and knowledge bases that enable team scalability.
• Evaluate and implement emerging AI technologies, frameworks (e.g., A2A, Deep Agents, Amazon Bedrock), and LLM providers to maintain competitive advantage.
• Design AI agent architectures and orchestration patterns that optimize advertising performance across channels.
• Build context engines, knowledge bases, and retrieval-augmented generation (RAG) systems for brand-specific optimization.
• Drive cost optimization strategies for AI/ML infrastructure while ensuring scalability and performance.
• Mentor and develop engineering talent, fostering a culture of technical excellence, innovation, and continuous learning.
• Collaborate with product management, data science, and other departments to align technical solutions with business objectives.
• Manage technical debt strategically, balancing short-term delivery with long-term sustainability.
• Support resource planning, technical hiring, and skills development within the engineering team.

Qualifications Required

• Extensive years of software engineering experience with at least 3 years in a senior or leadership role, preferably in performance media, digital marketing, or advertising technology.
• Deep expertise in AI/ML technologies including LLMs, prompt engineering, AI agents, and vector databases.
• Experience with AI orchestration frameworks such as Strands, LangGraph, A2A, or Amazon Bedrock Agents.
• Strong understanding of cloud services (AWS, Azure, or Google Cloud), containerization (Docker, Kubernetes), and serverless architectures.
• Experience with database design and management, including SQL databases, NoSQL solutions, and data warehousing.
• Proven track record of scaling MVPs to production systems with focus on cost optimization and performance.
• Excellent communication skills with ability to translate complex technical concepts for diverse stakeholders.

Preferred

• Experience with digital advertising platforms (Google Ads API, Meta Marketing API, Amazon Ads API) and programmatic advertising.
• Background in building multi-agent AI systems and retrieval-augmented generation (RAG) architectures.
• Experience with MLOps practices including model monitoring, A/B testing, and continuous model improvement.
• Familiarity with data engineering tools and practices for building analytics and optimization pipelines.

About the Way We Work

• Be You: We believe you should be able to be the same person at work as you are at home. Authenticity and trust are important. Be who you are, mean what you say, allow other teammates to do the same.
• Know Your Teammates: We know social opportunities reinforce relationships, and relationships shape our attitudes. Everyone is equal parts teacher and learner, so invest in each other. We are a community. Play with intention.
• Make It Better: We believe there's always room for growth—professionally, personally, and in our communities. We identify opportunities for improvement, innovation, and learning and encourage our clients to do the same.
• Collaborate Expertly: Everyone comes to us with a different background and provides unique value. Speak up, embrace a "what if" attitude, and support the people around you. Collaborate with your team, hone your expertise, and remember—the best idea wins.

We are dedicated to ensuring an inclusive environment where employees feel empowered to share their experiences and ideas. We encourage participation in a variety of Business Resource Groups, including groups for Women, People of Color, Veterans, the LGBTQIA community and allies, and more.