ai engineer for agentic experiences

Iterable is an AI customer engagement platform that helps organizations activate customer data, design cross-channel experiences, and optimize engagement. Its platform serves nearly 1,200 brands across more than 50 countries and includes Nova Intelligence, its AI layer.

• Design and build Machine Learning platform components for agentic systems, including retrieval pipelines, indexing strategies, and model integration layers
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns
• Develop evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring
• Implement abstractions, tooling, and reusable patterns that enable teams to build ML- and LLM-powered experiences
• Partner with backend engineers to productionize ML features with reliability, observability, and performance
• Prototype applied ML solutions to validate feasibility before full builds
• Ensure secure and robust handling of data in ML workflows and retrieval operations
• Collaborate with product, design, and engineering teams to align ML system design with user experience and product goals
• Improve the Nova agent framework, including workflows built with Mastra and TypeScript

• 5+ Years of experience as a Machine Learning Engineer or in a similar role focused on production systems
• Strong engineering skills in Python or TypeScript, including experience building ML workflows with Mastra or comparable agent/LLM toolkits
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures
• Experience integrating ML- or LLM-powered features into production applications
• Understanding of ML evaluation techniques, experimentation design, and failure analysis
• Ability to lead complex projects, make practical trade-offs, and work independently in ambiguous areas
• Strong communication and collaboration skills in a distributed environment
• Будет плюсом: ML or LLM platforms, tooling, or developer-facing frameworks; embeddings, search-ranking systems, or advanced RAG architectures; event-driven systems or streaming architectures; model observability, performance monitoring, or proactive regression detection; personalization, recommendations, or applied NLP; remote-first engineering teams

• Competitive salaries and meaningful equity
• Private Medical Insurance
• Life/Risk Assurance
• Meal Allowance: 8.55€ per day
• Community Days
• Paid Annual Leave (22 days)
• Global Lifestyle Reimbursement Account
• Paid Sabbatical
• Complete laptop workstation