Sr. Staff Software Engineer, Pinterest Assistant

Pinterest is a visual discovery platform that helps millions of people find inspiration and plan for the future, with AI playing an increasingly central role in its products. The Sr. Staff Backend Engineer will lead the architecture and technical direction of the Pinterest Assistant backend platform, including orchestration, personalization, memory, APIs, tool integrations, and infrastructure for scalable multimodal conversational experiences. The role also involves cross-functional technical leadership, engineering mentorship, and establishing best practices for production LLM and agent systems.

Responsibilities:

• Define and drive the technical vision and architecture for the backend systems powering Pinterest Assistant, ensuring they scale reliably as the product reaches millions of users
• Lead the design and implementation of the core Assistant platform including orchestration, memory and personalization, context management, APIs, tool integrations, and backend infrastructure
• Drive technical strategy, identifying foundational platform investments that unlock new Assistant capabilities while improving developer velocity, reliability, and scalability
• Partner closely with Product, Design, Frontend engineers, ML engineers, and Infrastructure teams to build a deeply personalized, multimodal conversational experience
• Shape the architecture for AI-powered applications, including retrieval, context assembly, tool execution, memory, and model orchestration, in partnership with ML teams
• Establish engineering best practices for production LLM and agent systems, including observability, logging, evals, safety mechanisms, rollout strategies, and incident response
• Mentor engineers, raising the technical bar through architecture reviews, technical guidance, and thoughtful engineering leadership
• Navigate ambiguity and make pragmatic architectural decisions that balance rapid product iteration with long-term maintainability
• Influence technical direction beyond the immediate team by collaborating across teams and helping shape Pinterest’s broader AI platform strategy
• Stay current with advances in LLMs, agentic systems, and backend platform design, and apply them pragmatically to consumer product development

Requirements:

• Bachelor's degree in a relevant field such as computer science or equivalent experience
• 10+ years of backend software engineering experience, including significant experience leading large, ambiguous systems that power consumer experience as a senior IC
• 3+ years operating as a technical lead, driving the architecture and development of large-scale distributed backend systems
• Strong backend engineering experience in Python, TypeScript, Node or similar languages and ecosystems
• Experience building platforms or foundational infrastructure that enables product teams to move faster
• Strong understanding of modern model-driven systems and experience partnering closely with machine learning engineers on AI-powered products
• Strong leadership, communication, and cross-functional collaboration skills
• Familiarity with concepts such as retrieval, ranking, personalization, inference, context management, or orchestration, with ability to collaborate effectively on technical design
• Track record of mentoring senior engineers and elevating engineering quality across an organization
• Product-minded and execution-oriented, with the ability to lead in ambiguity and move fluidly between strategy and hands-on implementation
• A strong builder's mindset: you know how to create momentum in ambiguous spaces, make pragmatic early decisions, and lay the technical foundation for systems that will grow in scale, complexity, and impact over time
• Experience building AI-powered or LLM-based products at scale
• Experience designing systems for conversational AI, agents, tool calling, or multimodal experiences
• Experience with retrieval, ranking, recommendation, search, or personalization systems
• Familiarity with embeddings, retrieval-augmented generation (RAG), context management, or memory architecture
• Experience partnering with Applied Scientists or Machine Learning engineers to bring ML capabilities into production
• Familiarity with evaluation frameworks, experimentation, and quality frameworks for AI products
• Full-stack development experience