Artificial Intelligence Specialist
Role details
Job location
Tech stack
Job description
- Optimize and Scale AI Tool Usage
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Maximize adoption and effectiveness of existing enterprise AI tools (e.g., Microsoft Copilot, Claude, ChatGPT).
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Design and deploy AI agents, workflows, and prompt frameworks with proper guardrails.
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Enable adoption across ~3,000 professional users through training, documentation, and practical solutions.
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Identify high-impact use cases and translate them into scalable AI-enabled workflows.
- Integrate AI with Enterprise Data
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Connect AI tools to structured and unstructured data sources, including enterprise data warehouses, ERP systems, and cloud-based document platforms.
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Build retrieval pipelines (RAG), APIs, and connectors that allow non-technical users to access data through AI-powered interfaces.
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Ensure data accessibility, reliability, and security within AI-driven solutions.
- Evaluate and Implement AI Technologies (Build vs. Buy)
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Assess commercial AI products and vendors against business requirements.
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Conduct build-vs-buy analyses and make recommendations based on ROI, scalability, and maintainability.
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Lead implementation of selected solutions across business units.
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Act as a trusted technical advisor in cross-functional and operational discussions.
- Develop Custom Applications and Automation
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Build and maintain custom AI-enabled applications where off-the-shelf solutions are insufficient.
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Develop production-grade systems using Python, SQL, and cloud-native technologies.
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Work within a modern cloud stack (e.g., Google Cloud Platform, including Cloud Run, Cloud SQL, Pub/Sub, Cloud Scheduler, Secret Manager).
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Leverage BigQuery, dbt, and CI/CD pipelines within a monorepo architecture.
Requirements
We are seeking a highly capable AI Solutions Engineer to drive the adoption, integration, and development of AI-powered tools across a large enterprise environment. This role blends hands-on engineering, data integration, product evaluation, and internal consulting. You will operate at the intersection of AI, data, and business operations-building solutions that make work more efficient, scalable, and impactful. This is a highly autonomous role requiring both technical depth and strong business communication skills., + Proven experience building, deploying, and maintaining production applications (Python and SQL required).
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Strong cloud experience (GCP preferred; AWS or Azure acceptable with willingness to adapt).
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Hands-on experience with:
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LLM APIs and prompt engineering
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Retrieval-Augmented Generation (RAG)
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Agent frameworks and AI workflows
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AI-assisted development tools (e.g., Copilot, Claude Code)
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Strong data expertise:
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Advanced SQL skills
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Experience with data warehouses and ELT pipelines
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Ability to work with complex, real-world datasets
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Ability to translate between technical and business stakeholders.
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Strong problem-solving skills with the ability to independently scope and deliver solutions.
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Sound judgment in evaluating when to build versus purchase solutions.
Preferred Qualifications
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Experience in construction, engineering, or operations-heavy industries.
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Familiarity with enterprise systems such as ERP (e.g., Viewpoint Vista) and HCM platforms (e.g., Workday).
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Experience with modern data stack tools (e.g., dbt, BigQuery).
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Experience building internal tools with enterprise authentication (e.g., Entra ID / OIDC).
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Demonstrated ability to drive adoption of new technologies among non-technical users.
Work Environment
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Full-time, in-office role (standard business hours).
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Collaborative, fast-paced environment focused on innovation and operational improvement.