10 hours ago
Remote, United States or Remote, CanadaStaff+
Responsibilities
- Design, build, and improve production-grade AI agent systems for web-based and chat-based marketing experiences.
- Architect agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring.
- Evaluate agent orchestration frameworks and patterns including Deep Agent, Claude Agent, OpenAI Agent, and LangGraph.
- Build and maintain LLM evaluation systems with LLM-as-judge workflows, regression evaluations, guardrail testing, quality metrics, and production behavior analysis.
- Diagnose agent performance across prompts, tool selection, retrieval quality, latency, cost, task completion, and failure modes.
- Design and implement RAG and embedding-based enterprise knowledge capabilities.
- Build scalable Python services and platform components deployed in AWS environments.
- Partner with product, platform, and engineering teams to turn agentic AI capabilities into reliable platform features.
- Establish engineering practices for continuous optimization of agentic systems and stay current with advances in LLMs, agent architectures, retrieval, evaluation, and enterprise automation.
Requirements
- Bachelor’s degree or higher in a quantitative field such as Statistics, Computer Science, Engineering, or 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 applying AI, data science, and machine learning in marketing.
- Experience using Adobe Experience Platform, Adobe Commerce/Magento, Adobe Real-time CDP, Adobe Target, and/or Adobe Analytics/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 in software development workflows.
- Strong engineering judgment, independence, and comfort operating as a senior individual contributor on ambiguous technical problems.
- Preferred qualifications include a master’s degree or higher, production LLM or AI agent experience, knowledge graph experience, enterprise automation experience, LLM observability and tracing, agent optimization, vector databases, search infrastructure, model routing, caching, and multi-model architectures.
Categories
About Netomi
Netomi builds an agentic AI platform for enterprise customer experience, automating support across chat, email, and voice through a no-code, SaaS model. Founded in 2016 and headquartered in San Mateo, it is used by global brands such as Delta Air Lines, United Airlines, and MetLife, and is backed by investors including WndrCo, Accenture Ventures, Adobe Ventures, Y Combinator, and Index Ventures.