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Data & AI Architect

Job in Elmhurst, Monroe County, West Virginia, USA
Listing for: Gerber Collision & Glass
Full Time position
Listed on 2026-07-19
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Engineering
Salary/Wage Range or Industry Benchmark: 145000 - 160000 USD Yearly USD 145000.00 160000.00 YEAR
Job Description & How to Apply Below
Location: Elmhurst

Company:
Gerber Collision & Glass

The Boyd Group welcomes unique talents from all backgrounds and characteristics. We act with integrity and appreciate the diverse perspectives that make our  Greater Team  exceptional. Qualified individuals, including those with disabilities and Protected Veterans, are encouraged to apply.

Job 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 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 is responsible for working collaboratively with the Head of Data & BI platform to develop and implement a coherent AI & data strategy.

Key Responsibilities Strategy, Roadmap & Innovation
  • Strategy:
    In collaboration with Head of Enterprise Architecture, Data Engineering, and BI to develop and execute AI & Data Strategy, 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 Dev Ex:
    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.
Minimum Education and Experience
  • 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 & 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).
Preferred

Education and Experience
  • Strategic Influence:
    You will help the Head of EA build the foundational strategy and roadmap for the entire department.
  • Innovation‑First:
    Encouraged to stay at the forefront of AI, implementing cutting‑edge protocols like MCP and Agentic systems.
  • Career…
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