AI Ops Lead

Kargo•New York, NY

About The Position

As the AI Ops Lead 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. 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

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

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

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume