Replit · San Francisco
Product & ProgramEngineeringRemoteFullTimeposted 5mo ago
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.
We're looking for an AI-native product growth lead to own Replit's entire paid acquisition and lifecycle marketing engine as the single DRI. This is an IC role for someone who builds systems, not just campaigns. Someone who uses AI and automation aggressively to do what traditionally requires an entire team. You don't need an engineering background. You need the instinct to build: when you see a repetitive task, you reach for Replit or an API before you reach for a spreadsheet.
You'll have data science and data engineering partners for infrastructure and modeling, and brand marketing will set creative direction. Your job is to turn that direction into a closed-loop optimization system: a self-improving system that turns performance data into better creative, optimizes spend across channels in near-real-time, and compounds every insight so nothing learned is ever lost. Each cycle, the system gets smarter. That's the engine you'll build and own.
The ideal candidate has deep channel expertise across paid search, paid social, and lifecycle, but their real edge is building AI-powered workflows that scale creative production, automate measurement, and compound institutional knowledge.
Own full-funnel performance marketing across paid search & social, ASO, and lifecycle
Build a self-improving creative engine: AI-driven ad generation, testing, and iteration that scales without scaling headcount
Maintain a persistent knowledge layer so every experiment, result, and creative insight compounds automatically into the next cycle
Own conversion signal quality end-to-end: right events, right audiences, right attribution, partnering with DE on the infrastructure
Run a structured experimentation program where every test feeds a feedback loop, not a one-off report
Automate performance reporting and alerting — your system flags problems (creative fatigue, CAC shifts, payback drift) before anyone has to ask
Build geo-differentiated strategies across market tiers and decompose performance by region before diagnosing aggregate shifts
Build the system that allocates spend, prioritizes tests, and rotates under-performers — the math makes the decisions; you build and own the engine that produces them
This is not a traditional marketing role. You'll operate more like a growth EM or PM who happens to focus on paid channels.
AI-First Execution: You automate before you do anything manually. Your primary tools are code, APIs, and AI workflows — not spreadsheets and platform UIs.
Systems Over Tasks: You build loops, not checklists. Every manual process is a candidate for automation; every insight feeds back into the system.
Strategic Partnership: You orchestrate brand, data science, and data engineering into a cohesive performance engine. Marketing feeds the system with creative direction and assets; you build the optimization loop that tests, scales winners, and returns performance insights to sharpen the next creative cycle.
Bias to Action: You ship fast, learn fast, and design experiments that generate the data you need rather than waiting for perfect information.
5+ years in performance marketing across at least two major paid channels (search, social, ASO, or programmatic)
Hands-on experience building AI-powered marketing workflows — not just prompting, but durable systems that run and improve on their own
Deep understanding of conversion tracking, attribution, and signal quality — you know the difference between filtering conversions and excluding audiences
Data-literate: comfortable with SQL, dashboards, and statistical rigor without needing a data team to interpret results
Track record managing significant budgets with clear ROI accountability
Strong experimentation instincts — structured test-and-learn programs, not one-off A/B tests
You've built your own tooling for marketing operations — bonus if you can show a portfolio of what you've built
Experience in developer-focused or PLG companies where paid and organic reinforce each other
You've thrived as a solo operator or on a very lean team
Comfortable with a modern data stack and warehouse-driven workflows
Hands-on experience with server-side conversion APIs and the postback lifecycle
You've brought measurement rigor and experimentation culture to a team that didn't have it before
You've scaled paid acquisition across geos with dramatically different unit economics
Managing a team—this is an IC role with leverage through systems, not headcount
Defining messaging, narrative, or creative strategy—Marketing owns what we say and how it looks; you own where it goes, how it performs, and what we learn from it
Building data pipelines from scratch—your DE partner handles infrastructure; you define requirements and consume the outputs
Sitting in meetings all day—we want someone who ships, not someone who presents
This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday.
Full-Time Employee Benefits Include:
💰 Competitive Salary & Equity
💹 401(k) Program with a 4% match (US Only)
⚕️ Health, Dental, Vision and Life Insurance
🩼 Short Term and Long Term Disability
🚼 Paid Parental, Medical, Caregiver Leave
🏝 Flexible Time Off (FTO) + Holidays
🚗 Commuter Benefits (In-Office & US Only)
📱 Monthly Wellness Stipend
🧑💻 Autonomous Work Environment
🖥 In Office Set-Up Reimbursement (In-Office Only)
🚀 Quarterly Team Gatherings
☕ In Office Amenities (In-Office Only)
Want to learn more about what we are up to?
Interviewing + Culture at Replit
To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.