Build and operate full-stack GenAI/ML-powered applications and services for Pinterest's Sales, Marketing, and Finance teams. Requires 10+ years software engineering experience, Python proficiency, production ML/LLM experience, and strong collaboration skills.
132k – 273k
Remote10+ YOEFullstack Engineering
About the role
What you’ll do
Design, build, and operate full-stack applications and services on Pinterest’s enterprise infrastructure to support our Sales, Marketing, and Finance teams, from backend services and APIs through integrations and user-facing workflows.
Lead the technical design and implementation of GenAI/ML-powered services and pipelines that automate and augment enterprise workflows (for example, summarizing sales interactions, enriching account data, or surfacing intelligent recommendations), including clear evaluation frameworks, observability, and validation guardrails.
Own the end-to-end software development lifecycle for these systems: requirements gathering, architecture, implementation, testing, deployment, monitoring, and continuous improvement.
Partner closely with product managers, business systems analysts, and other engineers to translate ambiguous business needs into well-defined technical plans, success metrics, and deliverables—and to make thoughtful tradeoffs between scope, risk, and speed.
Use AI coding tools and agents to accelerate development responsibly (e.g., drafting code and tests, iterating on designs, summarizing findings), while applying rigorous testing, code review, and observability to ensure quality and reliability.
Mentor and coach other engineers on system design, GenAI/ML patterns, and AI-augmented workflows, contributing to technical decision-making and raising the bar on engineering practices within the team.
What we’re looking for
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent combination of education and experience.
Experience building systems or analytics used by Sales and/or Marketing teams (for example CRM or sales productivity tools, campaign management and measurement, or revenue operations workflows), with a clear understanding of how these partners use data and tooling to hit their goals.
10+ years of software engineering experience building and operating production systems, including full-stack applications and/or backend services on a modern cloud platform (such as AWS or similar). Experience in enterprise or business systems environments is a plus.
Strong proficiency in Python and experience with at least one of: Java, Node.js, and/or Javascript, with a track record of delivering reliable, maintainable code in collaborative engineering teams.
Hands-on experience designing and operating distributed systems and robust, fault-tolerant integrations (e.g., REST/gRPC services, event-driven architectures, or data pipelines) that support critical business workflows.
Practical experience building or integrating GenAI/ML-powered features or services in production—such as LLM-based workflows, ML-driven recommendations, or intelligent automation—including an understanding of evaluation, observability, and common failure modes.
Demonstrated ability to use AI tools and agents to write, review, and validate detailed technical design documents (TDDs), specifications, and test plans as part of a spec-driven, agentic development workflow, while maintaining ownership of technical decisions, quality, and correctness.
Experience using GenAI coding tools (for example, Cursor, Claude Code, or similar) and/or agents in your development workflow, with a demonstrated ability to validate AI-assisted output and maintain high standards for quality, security, and maintainability.
Excellent communication, collaboration, and leadership skills, with the ability to work effectively across cross-functional, diverse teams and to explain complex technical concepts—including GenAI/ML tradeoffs—to non-technical partners.
Outcome-oriented mindset: you focus on delivering business outcomes rather than just technical outputs, using technology and AI thoughtfully to positively impact key performance metrics for Sales, Marketing, and Finance.
Salesforce engineering experience (for example, Sales Cloud, Service Cloud, or Salesforce integrations) is a plus, especially where it supports Sales and Marketing workflows.
Skills
PythonJavaNode.jsJavaScriptAWSGenerative AIMachine LearningLLMsSalesforceRestgRPCDistributed Systems
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