SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Netomi is a leading agentic AI platform for enterprise customer experience, working with major global brands like Delta Airlines, MetLife, MGM, and United to enable AI agent automation at scale across customer journeys. The company is backed by WndrCo, Y Combinator, and Index Ventures.
In this Staff-level role, you will design, build, and improve production-grade AI agentic systems optimizing web-based and chat-based customer experiences using grounded, structured data. You'll architect sophisticated agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring. Your responsibilities include evaluating emerging agent orchestration frameworks (Deep Agent, Claude Agent, OpenAI Agent, LangGraph) for marketing use cases, building LLM evaluation systems with LLM-as-judge workflows and regression testing, and diagnosing agent performance across prompts, tool selection, retrieval quality, latency, cost, and failure modes.
You'll design and implement RAG and embedding-based capabilities for enterprise knowledge access, build scalable Python services deployed in AWS, and partner with product and platform teams to translate emerging agentic AI capabilities into reliable platform features. The role requires establishing engineering best practices for continuous optimization and staying current with advances in LLMs, agent architectures, and enterprise automation.
Required qualifications include a Bachelor's degree in a quantitative field, 5-7+ years of AI/ML engineering experience, 3-5 years applying AI/ML in marketing, and strong Python skills for production systems. You must have hands-on experience with agent orchestration frameworks, RAG/embeddings, AWS deployment, and daily use of AI coding tools (Codex, Claude Code, Cursor). Preferred qualifications include a Master's degree, experience building production LLM/agent systems, knowledge graph modeling, AI evaluation systems, enterprise automation platforms, observability for LLM systems, and vector databases.
