[Remote] AI Solutions Engineer

Note: The job is a remote job and is open to candidates in USA. Pinterest is a platform focused on inspiring creativity and innovation among its users. They are seeking an AI Solutions Engineer who will partner with various teams to identify and implement AI-driven automation opportunities, transforming business processes through innovative AI tools and solutions.ResponsibilitiesDiscover and scope AI opportunities: Partner with internal teams across corporate functions to understand their workflows, pain points, and goals, and identify high‑value AI/automation opportunities. Map and improve business processes: document current workflows, identify bottlenecks, and propose AI‑enabled 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 AI‑enabled tools and workflows that integrate with existing systems and data sources, and that are intuitive for non‑technical usersBuild 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 timePilot, rollout, and drive adoption: Pilot, roll out, and drive adoption of solutions by working closely with end‑users, gathering feedback, and iterating based on real‑world usageChampion for responsible AI: Ensure solutions follow privacy, security, and compliance expectations, especially when working with sensitive or regulated dataBuild for reuse: Create and share reusable patterns, components, and documentation to make future AI/automation work faster and more consistent across teamsAccelerate 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)SkillsSoftware 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 applicationsHands-on AI and automation delivery. You've 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 systemAgentic 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 sufficeSystem 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 pathsData 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 afterBusiness 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 needsClear, 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-promisingExperience 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 toolingFamiliarity with MCP server design — including building, deploying, and securing MCP-compliant tool serversExperience designing and evaluating AI outputs at scale: eval sets, sampling pipelines, human-in-the-loop review queues, or A/B testing of AI-powered featuresExposure to responsible AI frameworks: data minimization, differential privacy concepts, model output auditing, or working in PII-sensitive / regulated domainsExperience with RAG (Retrieval-Augmented Generation) pipelines, vector databases, or enterprise search integrationsFamiliarity with CI/CD for AI: prompt versioning, model version pinning, regression testing for LLM-powered featuresBachelor's/Master's degree in a relevant field such as Computer Science or equivalent experienceDemonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputsStrong 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 deliverablesBenefitsThe position is also eligible for equity.Information regarding the culture at Pinterest and benefits available for this position can be found here.Company OverviewPinterest is a visual bookmarking tool for saving and discovering creative ideas. It was founded in 2010, and is headquartered in San Francisco, California, USA, with a workforce of 1001-5000 employees. Its website is https://www.pinterest.com/.