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Product Engineer, Marketing Innovation

  • $0K - $0K
  • San Francisco
  • Mid-level
  • On-site
  • Full time
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Salary

$0K - $0K

Location

San Francisco

Setup

On-site

Posted

3 months ago

AI/MLOn-site$180K-$240KFull-timeMid-levelProduct EngineeringRevenue Systems

The Challenge

OpenAI's Marketing Innovation team builds autonomous, AI-native systems that directly drive revenue and pipeline for enterprise customers. You'll own end-to-end product execution on agentic systems operating at massive scale-moving from ambiguous problems to production systems that measurably impact revenue.

Your Mission

First 3 Months
1

Ship your first autonomous customer-facing agent or internal workflow to production with instrumentation and performance baselines

2

Define success metrics and functional requirements by partnering with demand gen, sales, and marketing stakeholders on a 0-to-1 system

3

Become fluent in OpenAI's model APIs, orchestration tools, and evaluate tradeoffs between models and architectures for your systems

4

Build strong operational habits: monitoring, evals, iteration velocity, and making decisions based on live usage data

By 6 Months
1

Own 2-3 production agentic systems with measurable impact on enterprise pipeline, revenue, or marketing efficiency KPIs

2

Establish yourself as the go-to engineer for full-stack agentic product development (APIs, orchestration, frontend, deployment)

3

Contribute to defining new categories of AI-native marketing and revenue workflows; shape roadmap based on live product learnings

4

Mentor junior engineers on the team; document patterns and best practices for building reliable agents and automation at scale

KPIs You'll Own

Enterprise Pipeline Generated

Revenue-attributed pipeline created or influenced by your autonomous systems in a given quarter.

Agent Success Rate / Reliability

Percentage of autonomous workflows that execute correctly without human intervention; measured via instrumentation and evals.

Marketing Efficiency Gains

Time saved, cost per lead reduced, or volume handled by demand gen and marketing teams using your systems.

System Latency & Uptime

Production performance and availability of customer-facing and internal agentic systems; measured via monitoring dashboards.

Tools & Stack

OpenAI APIs (GPT-4, o1, etc.)PythonJavaScriptCloud infrastructure (AWS/GCP/Azure)Orchestration frameworks (e.g., LangChain, CrewAI, custom)Monitoring & observability (e.g., DataDog, New Relic)Git/GitHubSQL

Your Team

Your Manager

Head of Marketing Innovation (implied product/engineering leader)

Current Team

Cross-functional team of product engineers, embedded within Demand Gen and Marketing organization; close collaboration with sales, demand gen, and enterprise marketing stakeholders

New role; building out the team to scale autonomous, customer-facing agentic systems

The Package

Salary

$180K-$240K base

Equity

Likely (OpenAI employee stock options/equity package, not disclosed in posting)

Remote

On-site, San Francisco, CA. No remote flexibility mentioned; expect full-time, in-office presence required.

Benefits & Perks

Equity upside (private company, significant upside potential)
Health insurance (medical, dental, vision)
401(k) retirement plan
Learning and professional development budget
Work on cutting-edge AI systems and models
Competitive cash compensation in SF market

Company Intelligence

OpenAI is an AI safety and research company building large language models (GPT-4, o1) and products like ChatGPT. The company operates at massive scale, serving millions of users and thousands of enterprise customers. Marketing Innovation is a product engineering team tasked with building autonomous, AI-native systems that drive revenue and marketing efficiency.

Team Size

1001-5000

Customers

Enterprise customers, prospects, internal revenue and marketing teams

Culture

Fast-moving, product-driven, ownership-oriented. Low-process, high-impact. Focus on measurable business outcomes and operating at the frontier of applied AI.

Is This Role For You?

For You If
  • You've shipped 4+ years of user-facing or customer-facing software and want to own real systems with direct revenue impact
  • You love building 0-to-1 products in ambiguous spaces and enjoy defining problems as much as solving them
  • You're fluent in Python or JavaScript, comfortable full-stack, and excited to work with modern AI models and APIs
  • You thrive in fast-moving environments without groomed backlogs; you operate with strong ownership and care about measurable outcomes
  • You want to shape the future of AI-native marketing and revenue workflows at a company that is redefining what's possible with AI
Won't Work If
  • You require heavy process, detailed specs, and a groomed backlog before writing code; this role is ambiguous-to-execution
  • You lack hands-on production experience building, deploying, or operating complex systems (agents, automation, APIs at scale)
  • You're not interested in learning go-to-market, sales, or marketing workflows; this role is deeply embedded in revenue operations
  • You need flexibility to work remote; this is on-site in San Francisco only

Interview Process

1

Initial Screening Call

Phone or video conversation with recruiter to assess background, motivation, and fit with the team's charter.

2

Technical Deep Dive

Interview with 1-2 product engineers on the team; expect system design, agentic patterns, and discussion of past projects you've shipped.

3

Product Sense & Collaboration

Interview with a marketing or demand gen leader to assess your curiosity about go-to-market problems and ability to partner cross-functionally.

4

Leadership Interview

Conversation with Head of Marketing Innovation or VP of Marketing about vision, strategy, and long-term thinking around AI-native marketing systems.

5

Final Round (optional)

May include a brief take-home or design exercise focused on building an autonomous system for a marketing or revenue problem.

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Context

About Growth Marketing roles

Growth marketers drive user acquisition, activation, and retention through data-driven experimentation. They sit at the intersection of product, data, and marketing — running A/B tests, building funnels, and scaling what works.

A/B testingFunnel optimizationSQL & analyticsPaid acquisitionProduct-led growth
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