Overview As Principal Engineer, you define the long-term vision for indexing and retrieval infrastructure across Core, Ads, and Shopping to support fresh, high-quality candidate generation at scale. You lead modernization efforts, collaborate with cross-functional peers, and apply AI to accelerate design and verification. You mentor engineers and uphold reliability, safety, and cost efficiency. You will shape discovery experiences and contribute to Pinterest's AI-driven product strategy.
Compensation / Benefits- equity
- base salary range $285,452-$449,541 USD
- remote-friendly working model (PinFlex)
- in-office collaboration 1-2 times per quarter requirement
- inclusion and equitable workplace environment
Responsibilities- Define and drive the long-term technical vision for indexing and retrieval infrastructure across Core, Ads, and Shopping
- Lead cross-org modernization of the indexing architecture, enabling real-time and incremental retrieval at scale
- Partner with engineering, product, ML, and infrastructure leaders to align priorities and deliver shared platform capabilities
- Raise the technical bar through architecture reviews and complex platform changes spanning ingestion, indexing, retrieval, and quality evaluation
- Build shared platform capabilities (metrics, tuning surfaces, debugging workflows) to balance relevance, safety, engagement, revenue, and cost
- Mentor senior engineers and technical leaders, fostering inclusive collaboration and high operational standards
- Leverage AI to accelerate analysis, prototyping, and iteration on system design, while ensuring correctness and reliability
- Use AI to streamline repeatable work (summaries, design artifacts, platform insights) for faster high-impact decisions
Key requirements- Extensive experience building large-scale indexing, search, recommendation, or ads retrieval systems (real-time and incremental)
- Strong technical leadership across multiple teams or organizations
- Proven track record of leading modernization efforts (architectural convergence, legacy migrations, shared platforms)
- Exceptional systems thinking linking platform design to product quality, ML needs, and business outcomes
- Strong communication skills for senior technical and non-technical audiences
- Experience using AI to improve engineering workflows, with rigorous validation practices
- Accountability and integrity handling sensitive data and production-critical systems
- Bachelor's or Master's degree in Computer Science, Engineering, a related technical field, or equivalent experience.
- Strong communication with senior audiences
- Cross-functional collaboration
- Problem-solving and rigorous engineering judgment
- Large-scale indexing, search, or retrieval system design
- Real-time and incremental architecture
- Relevance tradeoffs and cost-efficient distributed infrastructure
