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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data & AI Architect - **Company:** Gerber Collision & Glass. - **Location:** Elmhurst, IL, United States - **Experience:** Experienced - **Salary:** $145,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon S3, Architectural Patterns, Automation of Tests, Cloud Computing, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Dataspaces, Data Warehousing, Distributed Computing Environment, Python (Programming Language), Machine Learning, Power BI, Azure Data Lake, Software Engineering, SQL Databases, Tableau (Software), Large Language Models, Snowflake, Prompt Engineering, Generative AI, Data Strategy, Qlikview, AWS Data Analytics, Data Management, Domo, Virtual Agents, Data Pipelines, Databricks - **Published:** July 12, 2026 - **Apply:** https://www.juju.com/job/00000000gfrxsg ## About the Role + AI Expertise: 2-3 years of hands-on experience with AI/ML implementations, focusing on GenAI patterns and LLM orchestration. + Data Engineering: 5+ years of experience in data architecture or engineering, with deep knowledge of data warehousing, lakehouses, and distributed processing. + Cloud & Tools: Strong proficiency in the AWS Data Stack , Python , and SQL . + Collaborative Execution: Ability to work with engineering teams to build the "plumbing" while working with business stakeholders to deliver the "intelligence." Required Knowledge, Skills, & Abilities + Industry Knowledge: awareness of the top AI solution providers and the rapidly evolving ecosystem of LLM providers and AI startups. + Advanced AI Patterns: Familiarity with AI-driven Software Development Life Cycle (SDLC) enhancements and testing automation. + Data & BI Ecosystem: Knowledge of leading platforms beyond the core stack, including: Data Platforms: Snowflake, Databricks, or Azure Data Lake, BI Tools: Power BI, Tableau, or Qlik. + Emerging Trends: Understanding of the shift toward natural language programming/orchestration (e.g., Vibe Coding) and standardized context sharing (MCP). ## Description The AI & Data Architect is a high-impact role responsible for accelerating our AI maturity and optimizing the data ecosystem that supports it. This role focuses on defining and implementing foundational elements for AI adoption - Architecture patterns ( Gen-AI, RAG, MCP, Agentic workflows etc.) , tooling, process & governance in collaboration with other stakeholders. This role will be key contributor to broad architecture of high-performance Data & BI platforms and solutions, ensuring Data platforms are key enablers of AI adoption journey The role reports to the Head of Ent. Architecture and is responsible for working very collaboratively with the Head of Data & BI platform, in order to develop and implement a coherent AI & data strategy. Key Job Responsibilities Strategy, Roadmap & Innovation + Strategy: In collaboration with Head of Enterprise Architecture, Data Engineering and BI to develop and execute AI & Data Strategy, in ensuring technical goals align with broader business objectives. + Roadmap Development: Build and maintain a multi-year AI/Data Roadmap , identifying key milestones for capability maturity, tool adoption, and infrastructure upgrades. + AI Solution Design: Design and implement architectural patterns for Generative AI, including Retrieval-Augmented Generation (RAG) , Model Context Protocol (MCP) , and Agentic AI frameworks. + Innovation & Modern DevEx: Explore the impact of AI on the software lifecycle, including AI-driven testing and emerging trends like "Vibe Coding" to accelerate development velocity. + Prototyping & PoCs: Lead Proof-of-Concept projects to evaluate new AI tools and techniques, moving successful experiments into production-ready environments. Data Platform & Governance + Modern Data Stack: Help define the evolution of the Data Platform architecture (AWS data ecosystem - S3, Lake Formation, Redshift, Airflow, Lambda) to ensure it is performant and "AI-ready." + Architecture Governance: Define and enforce best practices for AI security, prompt engineering standards, and the ethical use of machine learning models. + Pipeline Architecture: Design scalable ETL/ELT pipelines and data modeling strategies that support both real-time AI needs and historical BI reporting. + BI Optimization: Oversee the architectural health of our BI layers (e.g., Domo ) to ensure dashboards and self-service analytics are powered by clean, governed data. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)