AI Engineer

Kargo

New York (NY)

Hybrid

USD 140,000 - 180,000

Full time

14 days+

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Job summary

Kargo is seeking an AI Engineer for their New York office to architect and build AI-powered products. In this hybrid role, you will identify automation opportunities and work alongside various teams to enhance operations.

The ideal candidate has strong experience with AI automation, Python or JavaScript, and familiarity with platforms like Salesforce and Slack. The position offers a salary range of $140,000 - $180,000 USD.

Qualifications

  • Proficient in Python or JavaScript for custom connectors and scripting.
  • Hands-on with orchestration platforms such as n8n and Zapier.
  • Familiar with evaluation and observability frameworks for LLM applications.

Responsibilities

  • Architect, build, and scale AI-powered products and automations.
  • Identify high-value use cases and build intelligent workflows.
  • Own the strategic roadmap for AI operations.

Skills

Python
JavaScript
AI automation
SaaS APIs
Data & AI strategy

Education

5–8+ years in systems automation

Tools

LangGraph
n8n
Salesforce
Slack
Snowflake

Job description

Who We Are

Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our 600+ employees 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. Now 20+ years strong, Kargo 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.

Mission

As the AI Engineer at Kargo, you will architect, build, and scale AI-powered products and automations for Kargo’s commercial organization. Operating within the Data & AI team, you are 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.

Outcomes — What Success Looks Like in 6‑12 Months
  • At least 3 high-impact AI automations are live and actively used by commercial teams — measurably reducing manual work or improving data quality across Salesforce, Slack, or Snowflake
  • A governance model is in place covering prompt engineering standards, audit trails, and a feedback loop that drives continuous iteration
  • Cross‑functional stakeholders trust and use the tools you’ve built, and Kargo’s Data & AI leadership has a clear, prioritized AI Ops roadmap that you own and drive
  • You’ve established yourself as Kargo’s internal thought leader on applied AI — the person teams come to when they have a problem AI might solve
Skills — Core Capabilities
Design & Automation
  • 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
  • Translate business pain points into modular, extensible automation flows that are observable, debuggable, and fault‑tolerant; proficient in Python or JavaScript for custom connectors and scripting
  • 5–8+ years in systems automation, internal tools, or process/data engineering; hands‑on with orchestration platforms such as n8n, LangGraph, Zapier, or Make; strong familiarity with SaaS APIs and system interoperability
AI Agent Deployment
  • Build production‑grade LLM applications — agent workflows, retrieval systems, internal copilots — using ChatGPT Enterprise and related LLM APIs for knowledge surfacing, workflow routing, decision support, and dynamic content generation
  • Maintain a governance model for prompt engineering, agent testing, and audit trails; leverage AI‑assisted development tools (Claude Code, Cursor, Codex) to accelerate velocity; familiar with evaluation and observability frameworks for LLM applications
Internal Enablement & Strategy
  • 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
Nice to Have
  • Prompt libraries, embeddings‑based retrieval, or vector databases (Pinecone, Weaviate) and RAG pipelines
  • Retool or Streamlit for lightweight internal UIs; ArgoCD or Kubernetes CI/CD experience
Competencies — Behaviors We Like to See
Builder’s Instinct
  • Ships fast, iterates on real feedback, and knows when to build vs. buy — comfortable defining the problem and executing without a fully specified brief
Cross‑Functional Fluency
  • Translates between engineers and revenue leadership, earns trust by delivering things that work, and stays close to adoption after deployment
Bias for Impact
  • Prioritizes automations that move a real business metric and measures success by adoption and friction reduction — not lines of code
Ownership & Accountability
  • Owns the roadmap end‑to‑end, communicates proactively, flags blockers early, and treats internal users like customers
Growth Mindset
  • Stays current on the LLM and AI agent landscape, applies new tooling when it matters, and shares knowledge generously to raise AI fluency across teams

U.S Salary Range

$140,000 - $180,000 USD

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