Staff Agentic AI Engineer - Marketing

Logoslabs; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Netomi seeks a Staff Agentic AI Engineer to lead the design and deployment of production-grade agentic AI systems for enterprise customer experiences. You will shape workflows, tool use, retrieval, and guardrails across web and chat interfaces, collaborating with product and engineering teams to drive scalable, measurable automation.

You will bring deep experience with LLM-based agent architectures, RAG, embeddings, and observability, ensuring performance, cost, and reliability in real

Qualifications

• Bachelor’s or higher in Statistics, CS, Engineering, or Mathematics.
• 5–7+ years in AI/ML engineering, applied ML, NLP, or AI systems development.
• 3–5 years applying AI/data science in marketing.
• Experience with Adobe data tools for data science modeling.
• Strong Python engineering skills and scalable production software experience.
• Hands-on with agent orchestration frameworks like LangGraph or LangChain.
• Understanding of RAG, embeddings, retrieval quality, and knowledge-grounded generation.
• Experience deploying or operating systems in AWS cloud environments.

Responsibilities

• Design, build, and improve production-grade AI agentic systems for web and chat experiences.
• Architect agent workflows with reasoning, tool use, retrieval, guardrails, and monitoring.
• Evaluate agent orchestration patterns and frameworks for marketing use cases.
• Build and maintain LLM evaluation systems and regression testing.
• Diagnose agent performance issues across prompts, retrieval, latency, and costs.
• Develop RAG/embedding-based capabilities for enterprise knowledge access.
• Build scalable Python services in AWS and collaborate with product and engineering teams.
• Establish engineering practices for continuous optimization of agentic systems.
• Stay current with advances in LLMs and enterprise automation.

Skills

Python

LLM agents

LangChain

Agent orchestration

Performance debugging

Education

Bachelor’s Degree or higher in a quantitative field

Master’s Degree or higher

Tools

LangGraph

LangChain

AWS

Job description

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!

As a Staff Agentic AI Engineer at Netomi, you will be a senior individual contributor helping build the core agentic factory platform that will enable customers to agentically define and build customer-specific agents to expand marketing-oriented enterprise automation and brand interaction use cases. You will deliver innovative designs and implement reliable, scalable, and measurable agentic systems used by enterprise customers and business users in complex, real-world production environments.

This is a hands‑on engineering role for someone who drives innovation and has built production LLM and agent systems, understands modern agent architectures, and has strong instincts for evaluation, observability, performance diagnosis, and continuous optimization. You will work across agent orchestration, tool use, prompt and tool‑selection strategies, RAG, embeddings, guardrails, and LLM evaluation systems and marry these with appropriate deterministic and ML‑based solutions to expand Netomi’s agentic factory.

Responsibilities:

• Design, build, and improve production‑grade AI agentic systems that optimize web‑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, or multi‑model architectures