Marketing Engineer

DeepLearning.AI; Mountain View (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

DeepLearning.AI is seeking an engineer to own automation and agentic tooling across lifecycle marketing. You will architect AI-native workflows, integrate CRM and analytics tools, and build internal capabilities that let marketers deploy automations with minimal engineering support.

The role emphasizes hands-on work with LLM APIs, data pipelines, and event tracking, with a focus on delivering measurable reductions in manual work and reliable data for reporting.

Qualifications

• 3+ years as a software engineer, with 1–2 years applying that experience to marketing, growth, or RevOps
• Hands-on experience building with LLM APIs and agentic workflows
• Experience integrating or building on top of a CRM or marketing automation platform
• Working knowledge of SQL and comfort building or maintaining data pipelines
• Experience with event tracking and analytics tools
• Ability to translate a marketer's manual workflow into a clear technical specification, and ship it without heavy oversight

Responsibilities

• Design and build agentic workflows that automate lifecycle triggers, campaign QA, segmentation logic, and reporting
• Identify high-leverage marketing workflows to automate first
• Build internal tools to let non-technical marketers configure automations
• Evaluate new AI tooling and prototype applications for funnel problems
• Own the integration layer between Customer.io, Stripe, PostHog, and event data
• Support platform/data migrations with scripting and workflow recreation
• Build data pipelines for Metabase dashboards with Data Engineering
• Set up and maintain UTM, tracking, and attribution infrastructure
• Build infrastructure for A/B testing across lifecycle, email, and on-platform messaging
• Build self-serve reporting tools for marketing stakeholders

Skills

AI-native

Marketing engineering

LLM APIs

SQL

Event tracking

Technical spec to code

Tools

Customer.io

HubSpot

Braze

PostHog

Amplitude

Segment

Metabase

Stripe

Job description

What You Will Do:

Automation & 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
• 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

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

What You Bring:

Required

• 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
• 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.