AI Engineer

About Kargo

Kargo is a leader in building powerful connections between brands and consumers through innovative advertising experiences across premium digital platforms. With a team of over 600 employees and a creative science approach, Kargo continuously innovates to exceed industry benchmarks and client expectations. We have offices worldwide, including NYC, Chicago, LA, Dallas, Sydney, Auckland, London, and Waterford, Ireland.

Who We Hire

We seek tech-savvy individuals, creative designers, effective communicators, collaborative team players, data experts, and innovative product builders who are eager to shape the future of advertising technology.

Your Mission

As an AI Engineer at Kargo, you will architect, build, and scale AI-powered products and automations for our commercial organization. Working within the Data & AI team, you will be the crucial link between revenue teams and AI infrastructure. Your responsibilities will include identifying high-value use cases, building intelligent workflows and agentic applications, and deploying trustworthy systems across platforms like Salesforce, Snowflake, and Slack. You will be both hands-on in development and responsible for the strategic roadmap of 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

• Deploy at least 3 high-impact AI automations that are actively used by commercial teams, measurably reducing manual work or improving data quality in Salesforce, Slack, or Snowflake.
• Establish a governance model for prompt engineering, audit trails, and a feedback loop for continuous iteration.
• Ensure cross-functional stakeholders trust and utilize the developed tools, and that Kargo’s Data & AI leadership has a clear, prioritized AI Ops roadmap that you own and drive.
• Become Kargo's internal thought leader on applied AI, serving as the go-to expert for AI-related problem-solving.

Skills - Core Capabilities

Design & Automation

• Design, build, deploy, and maintain AI-powered automations and agent workflows using modern orchestration frameworks (e.g., 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, observable, debuggable, and fault-tolerant automation flows. Proficiency in Python or JavaScript for custom connectors and scripting.
• 5–8+ years of experience in systems automation, internal tools, or process/data engineering. Hands-on experience with orchestration platforms (e.g., n8n, LangGraph, Zapier, Make) and strong familiarity with SaaS APIs and system interoperability.

AI Agent Deployment

• Build production-grade LLM applications, including agent workflows, retrieval systems, and 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 (e.g., Claude Code, Cursor, Codex) to accelerate development. Familiarity with evaluation and observability frameworks for LLM applications.

Internal Enablement & Strategy

• Collaborate cross-functionally with Sales, Client Services, Media Strategy, Marketing, Product, and Ops to identify automation opportunities, prototype rapidly, document tooling, and drive self-service adoption.
• Own and communicate the AI Ops roadmap to Data & AI leadership, prioritizing by business impact, sequencing by feasibility, and grounding it in discovery with commercial teams.

Nice to Have

• Experience with prompt libraries, embeddings-based retrieval, or vector databases (e.g., Pinecone, Weaviate) and RAG pipelines.
• Experience with Retool or Streamlit for lightweight internal UIs; ArgoCD or Kubernetes CI/CD experience.

Competencies - Behaviors We Like to See

Builder's Instinct

• Ship features quickly, iterate based on feedback, and know when to build versus buy. Comfortable defining problems and executing without a fully specified brief.

Cross-Functional Fluency

• Bridge communication between engineers and revenue leadership, build trust through reliable delivery, and focus on adoption post-deployment.

Bias for Impact

• Prioritize automations that move key business metrics and measure success by adoption and friction reduction.

Ownership & Accountability

• Own the roadmap end-to-end, communicate proactively, flag blockers early, and treat internal users as customers.

Growth Mindset

• Stay current with the LLM and AI agent landscape, apply new tooling effectively, and share knowledge generously.

Compensation

• U.S. Salary Range: $140,000—$180,000 USD per year. Actual compensation may vary based on factors such as geographic location, work experience, education, and skills.

Our Laurels

• 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 Awards-Best CTV Platform
• Martech Breakthrough Awards-CTV Innovation
• Adweek Media Plan of the Year Awards - Best Use of Insights

Follow Our Lead

• Website: kargo.com
• Social Media: Instagram (@kargomobile) and LinkedIn (Kargo)

Equal Opportunity Employer

Kargo is an Equal Opportunity Employer committed to building an inclusive and diverse workplace. We do not discriminate on the basis of race, color, ethnic origin, religion or belief, sex, sexual orientation, gender identity or expression, age, disability, marital or family status, national origin, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants with arrest and conviction records for employment, in accordance with applicable fair chance laws.