AI Solutions Engineer

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 were 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 others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well 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.

Were building a new capability at Pinterest: embedding AI-native engineering directly inside our business functions. The AI Solutions Engineer will partner with teams across Marketing Finance Sales HR Legal and other functions to surface high-value automation opportunities then design and ship the AI-powered tools that bring those opportunities to life.

This is a hands-on mid-level software engineering role for someone who is equally comfortable reading a business process flowchart and writing production-grade Python. Youll work end-to-end from discovery and scoping through prototyping launch and iteration using the latest agentic frameworks tool-calling patterns and responsible AI practices.

What youll do:

• Discover and scope AI opportunities: Partner with internal teams across corporate functions to understand their workflows pain points and goals and identify highvalue AI/automation opportunities. Map and improve business processes: document current workflows identify bottlenecks and propose AIenabled changes that deliver clear business outcomes (e.g. time or cost savings improved quality or compliance).
• Design end-to-end AI solutions: Design and implement AIenabled tools and workflows that integrate with existing systems and data sources and that are intuitive for nontechnical users.
• Build and ship production-quality software: Write clean maintainable code and tests. Use standard CI/CD and environment practices. Implement logging monitoring and basic guardrails so we can understand and improve performance quality cost and reliability over time.
• Pilot rollout and drive adoption: Pilot roll out and drive adoption of solutions by working closely with endusers gathering feedback and iterating based on realworld usage.
• Champion for responsible AI: Ensure solutions follow privacy security and compliance expectations especially when working with sensitive or regulated data.
• Build for reuse: Create and share reusable patterns components and documentation to make future AI/automation work faster and more consistent across teams.
• Accelerate Workflows with Generative AI and Automation:Leverage AI to accelerate execution (e.g. draft prototype outline) explore alternative solutions using AI (iterate compare approaches) synthesize information with AI (summarize distill key themes) automate repeatable work (documentation reporting QA checks)

What were looking for:

Were looking for mid-level engineers who have already shipped something real with AI and who can work as a peer with non-technical business partners not just as an order-taker. Specifically you bring:

• Software engineering foundation. A CS Engineering Data Science or related degree (or equivalent experience) with demonstrated ability to build and operate production systems backend services internal tools integrations or data applications.
• Hands-on AI and automation delivery. Youve shipped AI-powered or automation-driven solutions in a real environment. Examples include: a multi-step workflow automation an internal tool using document understanding or intelligent routing or an integration of an AI service (e.g. OpenAI Anthropic Vertex AI Bedrock) into an existing system.
• Agentic AI literacy. You understand how modern agentic systems are constructed the difference between local and remote agents how MCP (Model Context Protocol) works what Agent Skills and Hooks are for and how A2A (Agent-to-Agent) coordination is structured. You can reason about when to use these patterns and when simpler approaches suffice.
• System design and architecture thinking. You can sketch a data flow reason about integration points evaluate trade-offs between approaches and design for failure including fallbacks retry logic timeouts and human escalation paths.
• Data and security judgment. You understand data access controls the risks of giving AI broad access to sensitive information PII minimization audit logging and what responsible data handling looks like in an enterprise environment. You know to filter data before it reaches the model not after.
• Business function acumen. You can engage credibly with stakeholders in Marketing Finance Sales HR Legal or Operations understanding their workflows KPIs and constraints well enough to scope solutions that fit their real needs.
• Clear collaborative communication. You can explain architecture trade-offs to a Finance Manager and debug a prompt failure with an engineer in the same afternoon. You build trust by being direct about limitations not by over-promising.
• Preferred Qualifications
  • Experience working embedded with or alongside corporate / G&A functions (Finance Legal HR Marketing Sales Operations or similar).
  • Practical experience with agentic frameworks such as LangGraph Claude Agent SDK or comparable tooling
  • Familiarity with MCP server design including building deploying and securing MCP-compliant tool servers.
  • Experience designing and evaluating AI outputs at scale: eval sets sampling pipelines human-in-the-loop review queues or A/B testing of AI-powered features.
  • Exposure to responsible AI frameworks: data minimization differential privacy concepts model output auditing or working in PII-sensitive / regulated domains.
  • Experience with RAG (Retrieval-Augmented Generation) pipelines vector databases or enterprise search integrations.
  • Familiarity with CI/CD for AI: prompt versioning model version pinning regression testing for LLM-powered features.
  • Bachelors/Masters degree in a relevant field such as Computer Science or equivalent experience.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • 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-reliance on AI and remain accountable for final decisions and deliverables.

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:

• This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country.
  
  

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