Full Stack Engineer – Marketing Tech, AI & Automation

About the Role

At Pavago, one of our clients — a fast-growing marketing agency serving 150+ home service businesses — is hiring a Full Stack Engineer to build and scale internal technology that directly supports marketing performance, lead generation, attribution, and revenue operations.

This is a hands-on builder role, not a strategy-only engineering position.

You’ll build production-ready internal tools using Next.js, React, and Python, connect advertising platforms with CRM and backend systems, improve marketing attribution, and integrate AI into real-world marketing workflows.

You’ll work closely with leadership, media buyers, and operators to turn operational problems into scalable technical solutions.

What You’ll Own

Internal Tool Development – Primary Focus

• Build and deploy internal applications using Next.js, React, and Python
• Develop dashboards, reporting systems, and operational tools for marketing teams
• Build production-ready systems that can scale across 150+ client accounts
• Replace manual processes with automated internal tools
• Maintain and improve existing applications as business requirements evolve

Marketing Data, Tracking & Attribution

• Implement and optimize Meta Pixel and Conversion API (CAPI)
• Manage event tracking, deduplication, and conversion attribution
• Build data pipelines connecting:
• Ad platforms
• Backend systems
• CRM platforms
• Reporting dashboards
• Improve accuracy between advertising data and actual lead/customer outcomes
• Build reporting systems around metrics such as:
• ROAS
• CPL
• CAC
• Conversion rates
• Lead quality
• Troubleshoot attribution and tracking discrepancies

CRM & Lead Lifecycle Automation

• Integrate and automate platforms such as:
• GoHighLevel
• Close CRM
• HubSpot
• Similar CRM systems
• Build workflows connecting lead capture → CRM → follow-up → conversion
• Automate lead routing, pipeline management, and lifecycle updates
• Sync CRM conversion outcomes back to advertising platforms through offline events/CAPI
• Ensure data remains accurate and consistent across systems
• Use APIs and webhooks to create reliable integrations between marketing platforms

AI Integration & Marketing Automation

• Build AI functionality directly into marketing and operational workflows
• Apply AI to use cases such as:
• Ad copy and creative generation
• Lead scoring and qualification
• Campaign analysis
• Automated reporting
• Operational workflow automation
• Work with APIs from OpenAI and similar AI platforms
• Build AI-powered systems that move beyond prototypes into real production workflows
• Identify repetitive processes that can be automated or accelerated with AI

Rapid Development & Iteration

• Ship quickly and iterate based on real campaign and user feedback
• Work directly with media buyers to identify technical bottlenecks
• Translate operational requirements into practical technical solutions
• Troubleshoot issues across applications, integrations, tracking, and automation
• Continuously improve systems that affect campaign performance and operational efficiency

Must-Have Experience & Skills

• 4–6+ years of hands-on software engineering experience
• Strong full-stack development experience with:
• React
• Next.js
• Python
• Proven experience building and deploying production-level applications and internal tools
• Strong experience working with APIs, webhooks, integrations, and automation systems
• Hands-on experience in a marketing technology, ad tech, agency, or performance marketing environment
• Experience implementing or managing Meta Pixel and/or Meta Conversion API (CAPI)
• Strong understanding of:
• Event tracking
• Deduplication
• Attribution
• Conversion tracking
• Experience building marketing dashboards and reporting systems
• Hands-on experience integrating CRM platforms such as GoHighLevel, Close CRM, HubSpot, or similar
• Experience automating lead capture, routing, pipelines, follow-ups, and conversion tracking
• Experience connecting advertising platforms with CRM data for attribution and reporting
• Active day-to-day use of AI tools and APIs
• Strong builder mentality with a bias toward shipping and execution
• Ability to work remotely during U.S. EST hours

Nice to Have

• Experience working directly inside a performance marketing agency
• Experience supporting paid media teams or media buyers
• Understanding of ROAS, CPL, CAC, conversion rates, and lead quality
• Experience with Zapier, Make, or similar automation platforms
• Experience designing and maintaining marketing data pipelines
• Understanding of attribution challenges caused by privacy changes and iOS tracking restrictions
• Experience building AI-powered internal tools
• Familiarity with multi-client or agency reporting environments

What Makes You a Strong Fit

• You’re a builder first — you enjoy turning problems into working software
• You understand engineering in the context of marketing performance and revenue
• You can move comfortably between frontend, backend, APIs, CRM systems, and marketing data
• You understand why accurate tracking and attribution matter to media buyers
• You use AI as part of your everyday engineering workflow
• You prefer shipping, testing, and improving over prolonged planning
• You can independently troubleshoot technical and operational problems
• You enjoy working directly with non-technical operators to build solutions they actually use

What a Typical Day Looks Like

You might start by reviewing a tracking discrepancy between Meta Ads and CRM conversions, then troubleshoot the event flow and CAPI implementation.

Later, you may build a Next.js dashboard for media buyers, create a Python service that automates campaign reporting, connect GoHighLevel data to an attribution pipeline, or integrate an AI model to score incoming leads.

You’ll regularly collaborate with media buyers and leadership, ship improvements, monitor how they perform in production, and iterate quickly.

In short: you build the technical infrastructure that makes marketing campaigns more measurable, automated, and effective.

What Success Looks Like

• Internal tools are actively adopted by media buyers and operators
• Manual campaign and CRM workflows are significantly reduced
• Tracking and attribution are accurate and reliable
• Ad platform and CRM data remain properly synchronized
• Campaign reporting becomes faster and more actionable
• Engineering solutions improve operational speed and efficiency
• AI-powered systems contribute to better lead quality and conversion performance