AI Enablement Engineer
Location: Charlotte, NC / Atlanta, GA / Minneapolis, MN / Irving, TX / Chicago, IL / Cincinnati, OH
Work Arrangement: Onsite – 5 Days a Week
Candidates located locally or within commuting distance of any USB Hub will be required to attend a face-to-face client interview.
Job Overview
We are seeking an experienced Enablement Engineer for a senior hands-on engineering role focused on accelerating the adoption of enterprise AI platforms across Lines of Business (LOBs).
This role is aligned with a designated CIO organization and is responsible for enabling the rapid delivery of high-value AI solutions. The position combines deep technical expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI with a focus on solution delivery, reusable implementation patterns, and enterprise enablement.
The ideal candidate will help ensure that AI solutions are scalable, secure, and compliant with organizational standards for responsible AI.
Key Responsibilities
-
Design, develop, and deploy Generative AI solutions from ideation through production.
-
Deliver high-value AI use cases through hands-on engineering and solutioning.
-
Guide engineering teams in effectively leveraging enterprise AI platform capabilities.
-
Drive adoption of enterprise AI platforms, including Azure AI, AWS Bedrock, and internal platforms.
-
Translate platform capabilities into practical and reusable implementation patterns.
-
Align AI use cases with enterprise AI strategy, standards, and governance requirements.
-
Serve as a liaison between centralized AI platform teams and CIO-aligned engineering teams.
-
Deliver training sessions, workshops, and technical guidance to engineering teams.
-
Develop enablement materials, including technical documentation, playbooks, and quick-start guides.
-
Upskill teams on GenAI techniques, including prompt engineering, RAG design, and orchestration frameworks.
Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)
- Minimum 5+ years of experience designing, developing, and deploying GenAI solutions from ideation through production
- Minimum 5+ years of experience delivering of high-value use cases through hands-on engineering and solutioning
- Minimum 5+ years of experience guiding teams in leveraging enterprise AI platform capabilities effectively
- Minimum 5+ years of experience driving adoption of enterprise AI platforms (e.g., Azure AI, AWS Bedrock, internal platforms)
- Minimum 5+ years of experience translate platform capabilities into practical implementation patterns
- Minimum 5+ years of experience aligning use cases to enterprise AI strategy, standards, and governance requirements
- Minimum 5+ years of experience serving as a liaison between centralized AI platform teams and CIO-aligned engineering teams
- Minimum 5+ years of experience delivering training sessions, workshops, and technical guidance to engineering teams
- Minimum 5+ years of experience developing enablement materials including documentation, playbooks, and quick-start guides
- Minimum 5+ years of experience upskilling teams on GenAI techniques such as prompt engineering, RAG design, and orchestration frameworks
Degree: Bachelors in Computer Science or equivalent work experience