Data & AI Architect

Company: Gerber Collision & Glass

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), tooling, process & governance— in collaboration with other stakeholders. The role will be a key contributor to the broad architecture of high‑performance data & BI platforms and solutions, ensuring data platforms are key enablers of the AI adoption journey.

The role reports to the Head of Enterprise Architecture and works collaboratively with the Head of Data & BI platform to develop and implement a coherent AI & data strategy.

• Develop and execute AI & Data strategy in collaboration with head of enterprise architecture, data engineering, and BI to align technical goals with business objectives.
• Build and maintain a multi‑year AI/Data roadmap, identifying milestones for capability maturity, tool adoption, and infrastructure upgrades.
• Design and implement architectural patterns for Generative AI, including Retrieval‑Augmented Generation (RAG), Model Context Protocol (MCP), and Agentic AI frameworks.
• Explore the impact of AI on the software lifecycle, including AI‑driven testing and emerging trends such as Vibe Coding to accelerate development velocity.
• Lead proof‑of‑concept projects to evaluate new AI tools and techniques, moving successful experiments into production‑ready environments.

• 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.
• Define and enforce best practices for AI security, prompt engineering standards, and the ethical use of machine learning models.
• Design scalable ETL/ELT pipelines and data modeling strategies that support both real‑time AI needs and historical BI reporting.
• Oversee the architectural health of BI layers (e.g., Domo) to ensure dashboards and self‑service analytics are powered by clean, governed data.

• 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, lake houses, and distributed processing.
• Cloud and 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 intelligence.

• 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 enhancements and testing automation.
• Data & BI ecosystem: knowledge of leading platforms beyond the core stack, including Snowflake, Databricks, Azure Data Lake, 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).

• Strategic influence: help the Head of EA build the foundational strategy and roadmap for the entire department.
• Innovation first: stay at the forefront of AI, implementing cutting‑edge protocols such as MCP and Agentic systems.
• Career growth: path to senior architectural leadership through high‑visibility projects and executive‑level collaboration.

$145,000 - $160,000 / Year

Compensation is commensurate with skill, education and experience.

Supplemental Pay: This position may also be eligible for bonus opportunities tied to individual or business initiatives.

• Annual Paid Time Off (PTO) plans
• 2 weeks of paid parental leave for full‑time employees who work a minimum of 30 hours per week
• 6 paid holidays annually
• Medical, prescription drug, dental & vision insurance…