Staff AI Agent Infra Engineer - Ads Platform

Pinterest, Inc.; San Francisco (CA); On-site; USD 208,000 - 365,000; Full time

Benefits offered by this job

In-office collaboration

Job summary

Pinterest, Inc. is seeking a Staff Software Engineer for the Ads Agent Infrastructure team to design and scale the stateful AI agent platform powering monetization and advertiser workflows.

You will steer architecture, platforms and runtimes that empower multiple engineering teams to deploy resilient agent-based processes. The role requires deep expertise in distributed systems, LLM agent frameworks, and security considerations, with a strong focus on observability and governance.

Qualifications

• At least 8 years in software engineering with distributed systems focus.
• Hands-on experience with LLM agent frameworks and runtime internals.
• Ability to set technical direction and align cross-functional teams.
• Experience with multi-tenant security and observability for AI systems.
• Proven track record of rigorous verification and code review.

Responsibilities

• Architect and maintain durable execution platforms for stateful AI agent workflows.
• Design MCP servers, SDKs and agent runtime interfaces for cross-functional adoption.
• Establish observability, tracing, versioning and cost governance for multi-agent systems.
• Drive technical strategy and write foundational infrastructure docs.
• Leverage AI to speed design, prototyping and documentation with quality controls.
• Automate testing, evaluation and grader pipelines for agent skills and memory services.

Skills

Distributed systems

LLM Agent

LangGraph

DeepAgents

Claude Agent SDK

Education

Bachelor’s or Master’s degree

Job description

Pinterest, Inc. is seeking a Staff Software Engineer for the Ads Agent Infrastructure team to design and scale the stateful AI agent platform powering monetization and advertiser workflows.

You will steer architecture, platforms and runtimes that empower multiple engineering teams to deploy resilient agent-based processes. The role requires deep expertise in distributed systems, LLM agent frameworks, and security considerations, with a strong focus on observability and governance.