Senior Data & AI Engineer

Material Bank is the world’s largest material marketplace for the architecture and design industry. They are seeking a Senior Data & AI Engineer to lead the design, development, and operation of AI agents that enhance intelligent experiences on their platform.

Responsibilities:

• Design, build, and operate production grade AI agents, owning the full lifecycle from prototyping and evaluation through deployment, monitoring, and continuous improvement
• Lead the development of scalable AI and data services, including MCP servers and REST APIs that expose intelligent capabilities to products, applications, and internal teams
• Serve as our internal expert on Snowflake Cortex, going deep on Cortex Agents, Cortex Analyst, and Cortex Search while partnering directly with Snowflake’s account and product teams to influence capabilities and shape how we apply the platform
• Apply modern agent architecture patterns including RAG, tool use, orchestration, memory, and evaluation frameworks to build reliable, accurate, and cost efficient AI systems
• Partner closely with Analytics & Insights team to design and maintain semantic and metrics layers that create consistent business definitions across AI, analytics, and reporting use cases
• Build and maintain scalable data pipelines, transformations, and models that power AI workloads using Snowflake, dbt, and Airflow
• Collaborate across data, product, analytics, and engineering teams to translate ambiguous business problems into well designed AI and data solutions
• Establish engineering standards and best practices for agentic systems, including observability, evaluation, prompt management, governance, and operational guardrails

Requirements:

• Deep experience and genuine passion for data engineering, with strong instincts around data modeling, pipeline architecture, scalability, data quality, and building reliable platforms. Strong data foundations are core to this role
• 5+ years of experience in data engineering, AI/ML engineering, or related fields, including recent hands on experience building and shipping LLM powered applications or AI agents into production environments
• Experience building production APIs and services, including MCP servers and REST based architectures
• Strong understanding of modern agent development patterns including RAG, vector search, prompt engineering, tool/function calling, and frameworks such as LangChain, LangGraph, or LlamaIndex
• Deep expertise in Snowflake, including performance optimization, warehouse architecture, and scalable data modeling approaches such as dimensional modeling or Data Vault
• Production experience with dbt and Airflow, including building and maintaining semantic or metrics layers
• Strong Python engineering skills and solid experience working within AWS environments including services such as S3, IAM, Lambda, ECS, or similar
• Hands on experience using AI powered engineering tools such as Claude Code or similar development accelerators as part of real world engineering workflows
• Excitement about specializing deeply in Snowflake Cortex and helping define our long term AI platform strategy
• Hands on experience working with Snowflake Cortex in production environments
• Experience with LLM evaluation, tracing, and observability platforms such as LangSmith, Arize, or Langfuse
• Experience partnering closely with analytics or BI teams to operationalize business metrics and semantic models
• Experience with Go, or a demonstrated ability to quickly learn and apply new technologies and programming languages