About the role
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.
The Conversion Visibility pod enables a performant ads marketplace and helps prove value to advertisers by connecting on-Pinterest intent with offsite conversions in a privacy-preserving way. We are hiring a Staff Software Engineer to lead the backend architecture and implementation of a GenAI-powered Conversion Health agent, using Event Quality Scores and conversion data to proactively detect issues, recommend and automate fixes, and demonstrate measurable performance impact for advertisers.
What you’ll do:
- Own the design and implementation of the Conversion GenAI agent: services, data flows, and retrieval layers that let agents reason over EQS, conversion funnels, and their impact on performance at scale.
- Evolve the existing GenAI Applications: harden prompts and tools, improve retrieval quality, add evaluation and safety checks, and make the agent reliable enough for always-on monitoring and decision support and make the impact on ad performance and efficiency clear.
- Design how the sub-agent connects with downstream ads products (PCL, ROAS bidding) and internal tools, including APIs, contracts, and workflows that surface product‑aware alerts and ranked recommendations to identify opportunities and power performance lifts.
- Consolidate and structure the measurement context layer—matched and attributed conversion tables, enrichment pipelines, and existing tools—into high-quality, AI-consumable signals the agent can query and reason over.
- Partner with Product, Operations, Sales, and other ads product teams to translate measurement pain points into agent skills (e.g., diagnosing EQS drops, PCL readiness, partner‑specific issues) and iterate quickly on internal-first experiences before expanding to advertiser-facing use cases.
- Lead an evolving GenAI culture and collaboration model across orgs: navigate ambiguity in a rapidly changing AI landscape to identify high-ROI patterns, codify pragmatic guardrails and workflows, and evolve how we collaborate so AI tooling translates into sustained gains in engineering velocity, measurement quality, and advertiser performance—not just isolated experiments.
What we’re looking for:
- 8+ years of backend or full-stack software engineering experience building large-scale distributed systems, services, and data pipelines, ideally in ads, measurement, or similar data-intensive domains.
- Proven track record shipping GenAI- or ML-powered products end-to-end (agent or model integration, retrieval, evaluation, safety/guardrails, and online/offline metrics).
- Required prior ads domain expertise, preferably in measurement, including conversion tracking, attribution, signal enrichment pipelines, and familiarity with concepts like ROAS, CPA, and campaign optimization. Strong bias toward business outcomes, with a track record of tying technical work to performance, measurement quality, and operational efficiency metrics.
- Strong proficiency in product scoping, data analysis and experimentation (e.g., SQL over large datasets, experiment design, cohort analysis) to connect conversion-health interventions to performance outcomes like ROAS, CPA, and PCL validity.
- Demonstrated technical leadership across teams: scoping ambiguous problems, aligning with product and XFN partners, and driving complex initiatives from vision through launch with clear documentation and communication.
- Experience upleveling engineers in AI tooling and best practices, including setting team-wide standards, templates, or processes for building and evaluating AI-assisted workflows.
- Bachelor’s degree in Computer Science, Engineering, a related field, or equivalent experience.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
- This role will need to be in the office for in-person collaboration 1 time per week and therefore needs to be in a commutable distance from one of the Seattle offices.
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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Aplyr's read
Pinterest is a hub for creative inspiration, attracting individuals passionate about visual discovery and digital content curation.
What's promising
- •Pinterest's unique visual discovery platform attracts a creative and engaged user base.
- •The company offers diverse roles, from engineering to creative strategy, indicating growth and innovation.
- •Pinterest's focus on machine learning and big data suggests a strong investment in technology.
What to watch
- •Pinterest faces stiff competition from other social media platforms like Instagram and TikTok.
- •Monetization challenges persist, particularly in converting user engagement into revenue.
- •The company's reliance on ad revenue makes it vulnerable to economic downturns.
Why Pinterest
- •Pinterest's platform centers on visual discovery rather than traditional social networking.
- •The company emphasizes user inspiration and idea curation over personal connections.
- •Pinterest's integration of machine learning enhances personalized content discovery.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Pinterest
Pinterest is a visual discovery engine that allows users to find and save ideas for various interests, including home decor, fashion, and recipes. By enabling users to curate and share their inspirations, Pinterest has become a significant platform for creativity and planning, impacting how people discover and engage with content online.
