Staff Agentic AI Engineer - Marketing

Netomi
United States
Remote

Who this role is best for

Strong fit for AI engineers with marketing domain expertise who build scalable systems and collaborate across teams.

Best fit for

  • AI engineers with marketing domain expertise and strong Python skills for building scalable systems
    — “Build scalable Python services and platform components deployed in AWS cloud environments”
  • Candidates with experience in agent orchestration frameworks and LLM evaluation systems
    — “Build and maintain LLM evaluation systems, including LLM-as-judge workflows, regression evals, guardrail testing, quality metrics, and production behavior analysis”
  • Individuals who have translated AI capabilities into enterprise marketing platform features
    — “Partner with product, platform, and engineering teams to translate emerging agentic AI capabilities into reliable platform features”

Things to consider

  • The role requires a high level of independence and problem-solving on ambiguous technical problems
    — “Comfort operating as a senior individual contributor on ambiguous technical problems”
  • There is a need to stay current with rapidly evolving AI technologies and frameworks
    — “Stay current with advances in LLMs, agent architectures, AI coding tools, eval methodologies, retrieval systems, and enterprise automation”

How to stand out

  • Highlight experience with agent orchestration frameworks like LangGraph and LangChain
    — “Hands-on experience with LangGraph, LangChain, or related agent orchestration frameworks”
  • Emphasize projects involving RAG and embedding-based enterprise knowledge systems
    — “Design and implement RAG and embedding-based capabilities for enterprise knowledge access and automation workflows”
  • Showcase ability to evaluate AI agent performance using LLM-as-judge methods
    — “Build and maintain LLM evaluation systems, including LLM-as-judge workflows”
  • Demonstrate experience with Adobe marketing platforms for data science modeling
    — “Experience leveraging data from Adobe Experience Platform, AdobeCommerce/Magento, Adobe Real-time CDP, Adobe Target, and/or AdobeAnalytics/Customer Journey Analytics”
  • Quantify impact of AI agent systems in marketing automation or customer experience
    — “Architect agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Designing and implementing agentic AI systems
  • Building scalable Python services
Typical background
AI/ML engineeringNatural Language Processing

Skills & requirements

Required

PythonLLM EvaluationAgentic AI SystemsAWS Cloud Environments

Preferred

Adobe Experience PlatformLanggraphLangchain

Stack & domain

PythonAIMLNLPLLMRAGEmbeddingsRetrievalKnowledge-grounded GenerationLanggraphLangchainAdobe Experience PlatformAdobecommerce/magentoAdobe Real-time CDPAdobe TargetAdobeanalytics/customer Journey AnalyticsAWS Cloud EnvironmentsAI Coding ToolsCodexClaude CodeCursorCollaborationCommunicationProblem-solvingEngineering JudgmentMarketingEnterprise Customer Experience

About the role

Original posting from Netomi via Lever

About the Company:

Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.

Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!

Responsibilities::

  • Design, build, and improve production-grade AI agentic systems that optimizeweb-based and chat-based experiences leveraging grounded, structured data
  • Architect agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring
  • Evaluate Deep Agent, Claude Agent, OpenAI Agent, LangGraph, and other emerging agent orchestration patterns and frameworks for marketing-oriented use cases
  • Build and maintain LLM evaluation systems, including LLM-as-judge workflows, regression evals, guardrail testing, quality metrics, and production behavior analysis
  • Diagnose agent performance issues across prompts, tool selection, retrieval quality, latency, cost, task completion, and failure modes
  • Design and implement RAG and embedding-based capabilities for enterprise knowledge access and automation workflows
  • Build scalable Python services and platform components deployed in AWS cloud environments
  • Partner with product, platform, and engineering teams to translate emerging agentic AI capabilities into reliable platform features
  • Establish engineering best practices for continuous optimization of agentic systems
  • Stay current with advances in LLMs, agent architectures, AI coding tools, eval methodologies, retrieval systems, and enterprise automation

Requirements::

  • Bachelor’s Degree or higher in a quantitative field (Statistics, Computer Science, Engineering, Mathematics)
  • 5-7+ years of experience in AI/ML engineering, applied machine learning, natural language processing, and/or AI systems development
  • 3-5 years of experience in applying AI, data science, and machine learning in the marketing space
  • Experience leveraging data from Adobe Experience Platform, AdobeCommerce/Magento, Adobe Real-time CDP, Adobe Target, and/or AdobeAnalytics/Customer Journey Analytics for data science modeling and performance analysis
  • Strong Python engineering skills and experience building scalable production software systems
  • Hands-on experience with LangGraph, LangChain, or related agent orchestration frameworks
  • Strong understanding of RAG, embeddings, retrieval quality, and knowledge-grounded generation
  • Experience deploying or operating systems in AWS cloud environments
  • Daily use of AI coding tools such as Codex, Claude Code, Cursor, or similar tools as part of software development workflows
  • Strong engineering judgment, ability to work independently, and comfort operating as a senior individual contributor on ambiguous technical problems

Preferred Qualifications::

  • Master’s Degree or higher in a quantitative field (Statistics, Computer Science,Engineering, Mathematics)
  • Experience building or using knowledge graphs for enterprise knowledge modeling,retrieval, reasoning, or personalization
  • Hands-on experience building production LLM or AI agent systems
  • Experience designing agent architectures involving tool use, reasoning flows, retrieval, memory, guardrails, and workflow orchestration
  • Experience developing AI evaluation systems, including LLM-as-judge, guardrail evaluation, regression testing, and production quality measurement
  • Experience with enterprise automation platforms, customer experience systems, workflow automation, or AI-powered business process automation
  • Experience with observability and tracing for LLM or agent systems
  • Experience optimizing agent systems for latency, cost, reliability, safety, and task success
  • Experience with vector databases, search infrastructure, model routing, caching, ormulti-model architectures

Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.

Source: Netomi careers (Lever)

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