Marketing Engineer

AI Fund; Mountain View (CA); In loco; USD 150.000 - 210.000; Tempo pieno

Descrizione del lavoro

DeepLearning.AI in Mountain View, CA is hiring a Marketing Engineer to architect automation and AI-driven tooling inside marketing. You will code, build agentic workflows, and integrate martech stack (Customer.io, Stripe, PostHog) to automate lifecycle, content, and reporting.

Reporting to Head of Marketing, you'll partner with AI engineers and marketers to ship production automations, design data pipelines for Metabase, and set up reliable tracking and attribution.

Competenze

• AI-native, default to using AI-assisted coding and building automations in everything you do.
• A minimum of 3 years experience as a software engineer, with 1–2 years applying that experience to marketing, growth, or RevOps problems
• Hands-on experience building with LLM APIs (Claude, OpenAI, or similar) and agentic workflows or tool-use patterns
• Strong scripting and integration skills (Python or JavaScript/Node) and comfort with REST APIs and webhooks
• Experience integrating or building on top of a CRM or marketing automation platform (Customer.io, HubSpot, Braze, or similar)
• Working knowledge of SQL and comfort building or maintaining data pipelines
• Experience with event tracking and analytics tools (PostHog, Amplitude, Segment, or similar)
• Ability to translate a marketer's manual, repetitive workflow into a clear technical specification, and ship it without heavy oversight

Mansioni

• Design and build agentic workflows that automate lifecycle triggers, campaign QA, segmentation logic, and reporting that the team currently does by hand
• Identify which marketing workflows are highest-leverage to automate first, in partnership with the Lifecycle Marketing Manager and Marketing Operations Coordinator
• Build internal tools that let non-technical marketers configure and launch automations without engineering support
• Continuously evaluate new agentic and AI tooling (Claude, other LLM APIs, automation platforms) and prototype how it applies to our specific funnel problems
• Own the technical integration layer between Customer.io, Stripe, PostHog, our platform's event data and any other tools we might use, so lifecycle triggers fire on accurate, real-time data
• Support various platform and data migrations with scripting, platform expansions, and workflow recreation as needed
• Build and maintain the data pipelines that feed our Metabase dashboard, partnering with Data Engineering to close our current LTV and cohort data gaps
• Set up and maintain UTM, tracking, and attribution infrastructure so channel performance data is trustworthy
• Build the technical infrastructure for A/B testing across lifecycle, email, and on-platform messaging, so the Lifecycle Marketing Manager and PMM team can test rigorously without engineering as a bottleneck
• Build self-serve reporting tools that let marketing stakeholders answer their own data questions without filing a ticket
• Where it's a natural byproduct of the automation work, document exciting or interesting builds for use in our content across newsletters, YouTube, events, or technical blogs
• Partner with Developer Relations when a build becomes a public case study or tutorial

Conoscenze

AI-native coding

Marketing automation

LLM APIs

Python

JavaScript/Node

REST APIs

SQL

Event tracking

Strumenti

Customer.io

HubSpot

Braze

PostHog

Stripe

Metabase

Descrizione del lavoro

Mountain View, CA

Deeplearning AI – Marketing

Full time

On-site

AI is the new electricity, transforming every aspect of our lives. DeepLearning.AI is on a mission to empower everyone to build with AI. We offer world-class education, hands-on training, access to AI news, a collaborative community and global in-person conferences.

We are looking for a Marketing Engineer to build the automation and AI-driven tooling that lets a small marketing team operate at the scale our growth goals require. This is a hands-on technical role embedded inside marketing. You will write code, build agentic workflows, and integrate our martech stack (Customer.io, Hootsuite, Stripe, PostHog) so that lifecycle, content, and reporting work that is manual today becomes automated and self-improving.

This role exists because we believe the next unlock for our team isn't more headcount doing manual work – it's state-of-the-art agentic techniques doing the work with just a bit of human involvement. As a natural extension of the work, you'll often be the most credible source on our team for what AI tooling can actually do today, which gives us a built-in story for our own content.

You will report to the Head of Marketing and work in an office collaborating with some of the most forward-thinking AI engineers building the next generation of technology.

What You Will DoAutomation & Agentic Tooling

• Design and build agentic workflows that automate lifecycle triggers, campaign QA, segmentation logic, and reporting that the team currently does by hand
• Identify which marketing workflows are highest-leverage to automate first, in partnership with the Lifecycle Marketing Manager and Marketing Operations Coordinator
• Build internal tools that let non-technical marketers configure and launch automations without engineering support
• Continuously evaluate new agentic and AI tooling (Claude, other LLM APIs, automation platforms) and prototype how it applies to our specific funnel problems

MarTech Integration

• Own the technical integration layer between Customer.io, Stripe, PostHog, our platform's event data and any other tools we might use, so lifecycle triggers fire on accurate, real-time data
• Support various platform and data migrations with scripting, platform expansions, and workflow recreation as needed
• Build and maintain the data pipelines that feed our Metabase dashboard, partnering with Data Engineering to close our current LTV and cohort data gaps
• Set up and maintain UTM, tracking, and attribution infrastructure so channel performance data is trustworthy

Experimentation Infrastructure

• Build the technical infrastructure for A/B testing across lifecycle, email, and on-platform messaging, so the Lifecycle Marketing Manager and PMM team can test rigorously without engineering as a bottleneck
• Build self-serve reporting tools that let marketing stakeholders answer their own data questions without filing a ticket

Dogfood & Content (Secondary)

• Where it's a natural byproduct of the automation work, document exciting or interesting builds for use in our content across our newsletters, YouTube accounts, events, or technical blogs. Note this supports the content engine but is not a primary deliverable or goal.
• Partner with Developer Relations when a build is interesting enough to become a public case study or tutorial

RequiredWhat You Bring

• AI-native, default to using AI-assisted coding and building automations in everything you do. Appetite, passion for and proven record of learning and experimenting with the newest AI engineering best practices.
• A minimum of 3 years experience as a software engineer, with at least 1–2 years applying that experience to marketing, growth, or RevOps problems
• Hands-on experience building with LLM APIs (Claude, OpenAI, or similar) and agentic workflows or tool-use patterns
• Strong scripting and integration skills (Python or JavaScript/Node) and comfort working with REST APIs and webhooks
• Experience integrating or building on top of a CRM or marketing automation platform (Customer.io, HubSpot, Braze, or similar)
• Working knowledge of SQL and comfort building or maintaining data pipelines
• Experience with event tracking and analytics tools (PostHog, Amplitude, Segment, or similar)
• Ability to translate a marketer's manual, repetitive workflow into a clear technical specification, and ship it without heavy oversight

Nice to Have

• Experience with Stripe or other subscription billing APIs
• Familiarity with Customer.io, Hootsuite, or Metabase specifically
• Experience writing technical content or documentation aimed at a developer audience
• Background in growth engineering, marketing ops engineering, or a similar hybrid role
• Familiarity with the AI/ML or technical education landscape

What Success Looks Like

In your first 30 days, you will have mapped our current martech stack and identified the highest-leverage manual workflow to automate first, plus you will have shipped your first automation into production, with a measurable reduction in manual work for the team and a documented build that can double as content. In 6 months, you will have built a durable automation layer across multiple marketing functions, established yourself as the team's go-to technical partner, and helped the team operate well beyond what its headcount alone would suggest is possible.

At DeepLearning.AI, we are committed to fostering a workplace of mutual respect and equal opportunity. We hire based on qualifications, merit, and business needs, without discrimination on any characteristic - whether protected by applicable laws or not. Our goal is to attract, recruit, develop, and retain the best talent from a diverse candidate pool.

$150,000 - $210,000 a year

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.