Sr. Staff Software Engineer, Pinterest Assistant

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.

We are looking for a passionate, inquisitive, and well-rounded Sr. Staff Backend Engineer to join the Pinterest Assistant team. The team is building a visual-first, AI-powered companion that helps Pinners go from inspiration to action across shopping, search, and discovery. As the technical leader for our backend platform, you will define the architecture and technical direction that powers our multi-modal, conversational experiences at scale. You’ll drive foundational investments across orchestration, memory and personalization, context management, tool integrations, APIs, and platform infrastructure, enabling the next generation of AI experiences. Working closely with Product, Design, Frontend, Infrastructure, and Machine Learning teams, you’ll shape the long-term technical strategy, raise the engineering bar across the organization, and build reliable, high-quality experiences that delight millions of Pinners. 

• →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.

• 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.
• Nice to have:
  • 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