AI Engineer

Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our dynamic teams work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world’s most premium platforms. Taking a Creative Science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Kargo is growing rapidly and currently has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. 

Who We Hire

Techies who want to build the future. Creatives who want to design it better. Communicators to win business. Collaborators to build it. Data pros who turn numbers into insights. Product builders who turn ideas into innovations. Anyone eager to be on a team that doesn’t stop to ask what’s next, because they’re already building it. 

The Opportunity

Kargo is hiring an AI Engineer to architect, build, and scale AI-powered products and automations for our commercial organization. Operating within the Data & AI team, you'll be the connective tissue between revenue teams and AI infrastructure—proactively identifying high-value use cases, building intelligent workflows and agentic applications, and deploying trustworthy systems across Salesforce, Snowflake, Slack, and other internal platforms. You're both hands-on and capable of owning the strategic roadmap for AI operations at Kargo. This is a hybrid role requiring onsite presence 4 days per week.

The Daily To-Do

• Design, build, deploy, and maintain AI-powered automations and agent workflows using modern orchestration frameworks—LangGraph, n8n, OpenAI Responses/Agents tooling, MCP-compatible architectures—with integrations across Salesforce, Slack, Snowflake, Atlassian, Google Workspace, Looker, and Airtable
• Build production-grade LLM applications—agent workflows, retrieval systems, internal copilots—for knowledge surfacing, workflow routing, decision support, and dynamic content generation
• Translate business pain points into modular, extensible automation flows that are observable, debuggable, and fault-tolerant
• Maintain a governance model covering prompt engineering standards, agent testing, audit trails, and feedback loops that drive continuous iteration
• Work cross-functionally with Sales, Client Services, Media Strategy, Marketing, Product, and Ops to discover automation opportunities, prototype quickly, document tooling, and drive self-service adoption
• Own and communicate the AI Ops roadmap to Data & AI leadership—prioritized by business impact, sequenced by feasibility, and grounded in real discovery with commercial teams