Staff Software Engineer, Agent Foundations

Confirmed live in the last 24 hours

San Francisco, CA, US; Remote, US

Hybrid

Posted March 30, 2026

Job Description

About Pinterest:

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.

We are looking for bold, technically deep Staff Backend Software Engineers to help define the future of the agent platform at Pinterest. Working closely with cross-functional engineering teams, product, and researchers, you'll play a pivotal role in architecting and scaling the systems that bring intelligent agent experiences to life. You will design and build the foundational platforms, from agent serving and evaluation to tracing and monitoring, that enable Pinterest's next generation of Agent capabilities. You will guide and empower engineering teams across the company, shaping how we build with and for agents at scale. Because we believe that transformative progress requires both technical rigor and courageous vision, you'll be invited to set direction, drive alignment, and lead initiatives from inception through technical design, implementation, and release.

What you'll do:

Define the technical direction and roadmap for Pinterest's agent platform, including critical components such as agent serving, evaluation, monitoring, and tool calling.
Design and build scalable, highly available infrastructure that supports production-grade agent services operating at company scale.
Partner with and advise internal product and engineering teams on agent tech stack needs, shaping the future vision of the agent platform.
Lead day-to-day technical alignment across teams, driving execution on key agent infrastructure investments and complex cross-functional platform initiatives.
Use AI to accelerate system design, prototyping, and technical decision-making, applying sound judgment to validate outputs and ensure correctness and quality.
Synthesize emerging research and advances in agent technology, translating breakthroughs into actionable platform improvements.

What we're looking for:

2+ years of experience building agent systems, with a strong understanding of core agent platform components such as memory, serving, evaluation, harnesses, and tool calling.
7+ years of experience building scalable, highly available backend systems, including designing and operating infrastructure that supports production-grade services at scale.
Experience with cloud-native infrastructure and service deployment technologies such as Kubernetes and Docker, with a strong understanding of how to deploy and manage large-scale services reliably.
Demonstrated technical leadership in setting roadmap and driving execution — including defining technical direction, leading engineering alignment, and partnering across teams to deliver complex platform investments.
Demonstrated ability to use AI to accelerate development, system design, and decision-making, with sound judgment in validating outputs, maintaining quality, and taking ownership of final outcomes.
Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
High integrity and ownership: you protect sensitive data, avoid over-relian