Principal Engineer, Shopping & Delivery Infra

What you’ll do

• Define and drive the long-term technical vision for indexing and retrieval infrastructure across Core, Ads, and Shopping, aligning architecture investments to measurable improvements in freshness, quality, coverage, reliability, and cost efficiency.
• Lead cross-org initiatives to modernize Pinterest’s indexing architecture, including advancing unified real-time and incremental retrieval systems that support high-scale, high-quality candidate generation.
• Partner closely with engineering, product, ML, and infrastructure leaders to align priorities, resolve tradeoffs, and deliver shared platform capabilities that improve retrieval performance across multiple discovery surfaces.
• Raise the technical bar for retrieval infrastructure by guiding system design, architecture reviews, and execution on complex platform changes that span document ingestion, indexing, retrieval, and quality evaluation.
• Build shared platform capabilities such as common metrics, tuning surfaces, and debugging workflows that help teams understand and improve the tradeoffs between relevance, safety, engagement, revenue, and infrastructure cost.
• Mentor senior engineers and technical leaders across teams, fostering strong engineering judgment, inclusive collaboration, and high standards for operational excellence.
• Use AI to accelerate analysis, prototyping, and iteration on system design options, while applying engineering judgment and verification to ensure correctness, reliability, and quality.
• Use AI to streamline repeatable work such as summarizing technical investigations, drafting design artifacts, and synthesizing platform insights so teams can move faster on high-impact decisions.

What we’re looking for

• Deep expertise building and evolving large-scale indexing, search, recommendation, or ads retrieval systems, including real-time and incremental architectures, relevance tradeoffs, and cost-efficient distributed infrastructure.
• Strong technical leadership experience operating across multiple teams or organizations, with a track record of influencing direction, aligning stakeholders, and driving complex platform decisions to completion.
• Proven ability to lead large modernization efforts such as architectural convergence, migration from legacy systems, rollout of shared platforms, or introduction of new infrastructure capabilities at scale.
• Exceptional systems thinking and problem-solving skills, with the ability to connect platform design decisions to downstream product quality, ML needs, operational health, and business outcomes.
• Strong communication skills, including the ability to distill complex technical topics for senior technical and non-technical audiences, and to drive clarity in ambiguous, high-impact spaces.
• Demonstrated experience using AI to improve speed and quality in day-to-day engineering workflows, such as technical analysis, prototyping, design exploration, documentation, or synthesis of complex information.
• Strong track record of critically evaluating and validating AI-assisted work through testing, source-checking, peer review, and sound engineering judgment, with clear accountability for final decisions and deliverables.
• High integrity, ownership, and care in handling sensitive data and production-critical systems, including thoughtful use of AI without over-reliance and with strong attention to privacy, safety, and correctness.
• Bachelor’s or Master’s degree in Computer Science, Engineering, a related technical field, or equivalent experience.