Material Bank - Senior Data & AI Engineer
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. • What you’ll get from us: • Our people: We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. • Our people • Relaxation and Celebrations: Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). • Relaxation and Celebrations • Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
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. • 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.
Benefits
• Plan for your Retirement: 401(k) eligible after your first 90 day's employed! • Plan for your Retirement • Giving Back: We sponsor multiple events throughout the year to help out our communities. • Giving Back • Growth: We’ll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! • Growth • Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. • Flexible Work Schedules • hybrid working
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