Staff Agentic AI Engineer

🕒 August 4

🇨🇦 Canada – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Netomi

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 $30M Series B on 2021-11

Consulting • Logistics • Marketing

Netomi is a company that specializes in providing AI-powered customer experience solutions. Their platform, known as Agentic OS, is designed for enterprise-scale customer service and integrates seamlessly with existing business systems. Netomi's solutions leverage generative AI and large language models to automate over 80% of customer inquiries, enhance customer satisfaction, and reduce support costs. Netomi is trusted by global brands across various industries, offering secure, proactive, and predictive customer care through omnichannel support, including email, chat, messaging, SMS, social media, search, and voice. The company ensures compliance with stringent security standards and data protection regulations.

📋 Description

• Design, build, and improve production-grade AI agentic systems for Netomi’s core platform • 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 new use cases • Build and maintain LLM evaluation systems, including LLM-as-judge workflows, regression evaluations, 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, evaluation methodologies, retrieval systems, 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 • 2+ years of hands-on experience building production LLM or AI agent systems • Demonstrated experience building agents used in production by external customers or enterprise/business users • Hands-on experience with LangGraph, LangChain, or related agent orchestration frameworks • Experience turning messy, unstructured source material into validated structured output using schemas, ontologies, or data contracts with entity resolution, disambiguation, and conflict resolution • Strong Python engineering skills and experience building scalable production software 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 • 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, ability to work independently, and comfort operating as a senior individual contributor on ambiguous technical problems