Build and optimize production-grade agentic AI systems for marketing and enterprise customer experience use cases. Responsibilities include agent orchestration, tool use, RAG, embeddings, guardrails, LLM evaluation, observability, performance optimization, and scalable Python services deployed on AWS. The role partners across product and engineering teams and requires hands-on experience with LLM agents, marketing data platforms, retrieval systems, and AI evaluation.
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, 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 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 modern 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.
Responsibilities:
- 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
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, ormulti-model architectures
Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
Similar Jobs
Professional Services • Consulting
Researches and builds agentic AI capabilities for marketing workflows, combining experimental development with production delivery. Evaluates models and orchestration frameworks, develops knowledge graphs for recommendations and personalization, integrates marketing data platforms, and creates LLM evaluations, observability, and performance diagnostics. The role also identifies emerging AI capabilities and requires expertise in applied machine learning, NLP, agent frameworks, retrieval-augmented generation, embeddings, and marketing analytics.
Top Skills:
Adobe AepAdobe AnalyticsAdobe CdpContentfulEmbeddingsGrounded GenerationKnowledge GraphsLangchainLanggraphLarge Language ModelsPythonRetrieval-Augmented GenerationTealium
Cloud • Security • Software • Cybersecurity • Automation
Lead hands-on product security architecture across GitLab, including design reviews, threat modeling, systemic risk remediation, security standards, prototypes, and reusable developer guardrails. Partner with engineering and product leaders, secure distributed systems and software supply chains, guide AI coding tool security, mentor security engineers, and influence technical direction through proactive architecture and clear communication.
Top Skills:
Ai Coding ToolsApplication SecurityDevsecopsDistributed SystemsSoftware Supply Chain SecurityThreat Modeling
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Own the full outbound sales cycle for mid-market merchants, from prospecting and pipeline development through discovery, product demonstrations, negotiation, and close. Build net-new business through strategic outreach, sell multi-product solutions, manage complex multi-stakeholder deals, forecast accurately in Salesforce, and consistently exceed revenue targets. Collaborate with business development, product, marketing, implementation, and operations teams while serving as a consultative advisor to merchants.
Top Skills:
Salesforce
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
