AI Engineer – Marketing Intelligence & Automation

Role Overview

The AI Engineer will design and deploy AI agents, integrations, data pipelines, and orchestration workflows to connect marketing data and automate processes, creating a scalable system for marketing intelligence.

What You Will Do

You will build AI agents and agentic workflows, marketing intelligence infrastructure, API and platform integrations, retrieval and knowledge systems, predictive and next-best-action capabilities, digital journey orchestration, conversational AI, measurement, attribution, and forecasting, content and publishing automation, and search and AI visibility automation.

Why It Might Be a Fit

The ideal candidate is a systems thinker who can translate business problems into technical designs, prototypes, and production systems, with experience in AI engineering, software engineering, data engineering, or a similar role.

Requirements

• 4+ years of experience in AI engineering, software engineering, data engineering, ML engineering, marketing engineering, or a similar role building production technical systems.
• Strong programming skills in Python and experience with JavaScript/TypeScript or another modern application language.
• Hands-on experience building with LLMs, including APIs, tool/function calling, structured outputs, prompt design, agent frameworks, and production evaluation.
• Experience designing RAG or enterprise knowledge-retrieval systems, including embeddings, vector search, metadata, chunking, permissions, and source grounding.
• Experience building data pipelines, APIs, event-driven integrations, and workflow automations across SaaS and enterprise platforms.
• Working knowledge of cloud architecture and data platforms; experience with AWS and Amazon Redshift is particularly relevant.
• Understanding of data modeling, identity resolution, data quality, observability, security, access controls, and governance.
• Experience with marketing technology, CRM, CMS, analytics, digital experience, or marketing automation platforms is strongly preferred.
• Able to translate ambiguous business problems into technical designs, prototypes, production systems, and measurable outcomes.
• Clear communicator who can explain architecture, tradeoffs, risk, and business impact to both technical and non-technical partners.
• Comfortable testing emerging AI capabilities while applying appropriate controls for accuracy, privacy, security, and brand risk.
• Experience in B2B, enterprise software, financial technology, or regulated environments is a plus.

Benefits

• Medical, dental, and vision coverage
• 401(k) plan with company match
• Paid time off, holidays, and parental leave
• Professional development reimbursement opportunity

Tagged as: Forecasting, Python