Asks for

The ad says“Experience building production-grade LLM applications using ChatGPT Enterprise and related LLM APIs, including familiarity with evaluation and observability frameworks”
The ad says“Fluency with AI-assisted development tools (Claude Code, Cursor, Codex) to accelerate velocity”
The ad says“Fluency with AI-assisted development tools (Claude Code, Cursor, Codex) to accelerate velocity”
The ad says“Fluency with AI-assisted development tools (Claude Code, Cursor, Codex) to accelerate velocity”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“Proficiency in Python or JavaScript for custom connectors and scripting, with strong familiarity with SaaS APIs and system interoperability”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“Experience building production-grade LLM applications using ChatGPT Enterprise and related LLM APIs, including familiarity with evaluation and observability frameworks”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“Proficiency in Python or JavaScript for custom connectors and scripting, with strong familiarity with SaaS APIs and system interoperability”
The ad says“Proficiency in Python or JavaScript for custom connectors and scripting, with strong familiarity with SaaS APIs and system interoperability”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”
The ad says“5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make”

Values

The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”
The ad says“Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience”

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
Serve as Kargo's internal thought leader on applied AI—staying current on the LLM and agent landscape and sharing knowledge generously to raise AI fluency across teams

Qualifications

5–8+ years in systems automation, internal tools, or process/data engineering, with hands-on experience in orchestration platforms such as n8n, LangGraph, Zapier, or Make
Proficiency in Python or JavaScript for custom connectors and scripting, with strong familiarity with SaaS APIs and system interoperability
Experience building production-grade LLM applications using ChatGPT Enterprise and related LLM APIs, including familiarity with evaluation and observability frameworks
Fluency with AI-assisted development tools (Claude Code, Cursor, Codex) to accelerate velocity
Proven ability to translate between engineers and revenue leadership, earning trust by delivering things that work and staying close to adoption after deployment
A builder's instinct and bias for impact—ships fast, iterates on real feedback, knows when to build vs. buy, and measures success by adoption and friction reduction, not lines of code
Nice to have: prompt libraries, embeddings-based retrieval or vector databases (Pinecone, Weaviate), RAG pipelines, Retool or Streamlit for lightweight internal UIs, and ArgoCD or Kubernetes CI/CD experience

In accordance with applicable federal, state, and local pay transparency laws, the anticipated base salary range for this position is listed below. In addition to base salary, this role is eligible for variable compensation — either the Kargo Sales Incentive Plan (sales roles) or an annual discretionary bonus (all other roles). Actual compensation may vary based on factors such as geographic location, work experience, education, and skills.

U.S Salary Range

$140,000—$180,000 USD

What We're Proud Of

AdAge Best Places to Work
ThinkLA Partner of the Year
Built In Best Places to Work
Cynopsis 2025 Top Women in Media - Jeannine Shao Collins
Martech Breakthrough Awards - Best Overall Adtech Company
Digiday Media Awards Best Event
Cynopsis Media Impact Awards-Best CTV Platform
Martech Breakthrough Awards-CTV Innovation
Adweek Media Plan of the Year Awards - Best Use of Insights

Following Our Lead

Big Picture: kargo.com
The Latest: Instagram (@kargo.hq) and LinkedIn (Kargo)