AI Engineer

Kargo•New York, NY

4d•Hybrid

About The Position

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.

Requirements

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
Proficient in Python or JavaScript for custom connectors and scripting

Nice To Haves

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

Responsibilities

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
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
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