Who you are

- 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

- Robust 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

- 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

What the job involves

- As a Staff Agentic AI Engineer at Netomi, you will be a senior individual contributor helping buildthe core agentic factory platform that will enable customers to agentically define and buildcustomer-specific agents to expand marketing-oriented enterprise automation and brandinteraction use cases

- You will deliver innovative designs and implement reliable, scalable, andmeasurable 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 productionLLM and agent systems, understands contemporary agent architectures, and has strong instincts forevaluation, observability, performance diagnosis, and continuous optimization

- You will workacross agent orchestration, tool use, prompt and tool-selection strategies, RAG, embeddings,guardrails,



and LLM evaluation systems and marry these with appropriate deterministic andML-based solutions to expand Netomi’s agentic factory

- 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

Benefits

- Flexible work environments
- Educational / professional development opportunities

- Equity opportunities
- 401K plan

- Snacks, breakfast and a daily catered lunch

- Work from home opportunities

- Health insurance

📌 Staff Agentic AI Engineer (Toronto)
🏢 Netomi
📍 Toronto