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AI Enablement Engineer

Role overview

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
  • 5+ years of progressive AI/ML engineering experience including hands-on LLM development.
  • Deep understanding of LLM internals.
  • Strong collaboration and communication skills.

Responsibilities

  • Evaluate and integrate LLMs and AI tooling.
  • Partner with rapid prototyping developers to shape AI-driven product features.
  • Develop advanced prompt engineering techniques and automate workflows.
  • Establish and report adoption and impact metrics.

Key facts

  • Remote from: Ohio (USA)
  • Full time
  • Senior (5-10 years)
  • AI Engineer
  • English

Hard skills

Other skills

  • Mentorship
  • Problem Solving
  • Analytical Thinking
  • Detail Oriented
  • Communication

About the company

MediQuant logo

MediQuant

Digital Health & Health Tech

MediQuant offers the industry's leading enterprise active data archiving platform along with unparalleled data migration and extraction experience to help you maximize your technology investments while getting the most value from your data. Make better decisions, faster. Ensure compliance. Shed unnecessary cost. Apply technology and the right subject matter expertise to achieve best-practice stewardship of data.

Company details

Company typeSME
IndustryDigital Health & Health Tech
Company size51 - 200

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Job description

POSITION TITLE: AI Enablement Engineer 

Supervised by: Director of Software Development 

Supervises: N/A 

FLSA Status: Exempt / Full-Time

POSITION SUMMARY. The AI Enablement Engineer is a senior-level, hands-on technical leader responsible for enabling the rapid development of secure and scalable AI capabilities across enterprise products. This role specializes in LLMs, prompt engineering, and AI-driven automation techniques, collaborating closely with rapid prototyping developers, architects, and security experts to ensure AI solutions integrate effectively with enterprise systems. This role will directly improve implementation velocity by automating data mapping, loading, validation and related workflows and will champion responsible enterprise adoption of AI tools and operational workflows across the organization.

JOB DUTIES and ESSENTIAL FUNCTIONS. A qualified individual must be able to perform these essential functions of the job as listed, with or without accommodation.

  1. AI Platform Evaluation and Solution Design
    1. Evaluate, recommend, and integrate LLMs and AI tooling, including platform selection guidance (e.g., OpenAI, Anthropic, Azure OpenAI, Hugging Face, and comparable enterprise AI platforms / tools). When AI tooling affects client onboarding, data migration, or conversion workflows, partner with Implementation Services and Data Engineering leadership to assess feasibility and operational impact.
    2. Provide technical evaluation input on feasibility, security posture, architecture fit, integration complexity, and total cost of ownership within a build vs. buy vs. partner framework owned jointly by Product Management and Implementation Services leadership. This role informs the business case; it does not own ROI sign-off.
    3. Collaborate with technical architecture to ensure AI solutions align with enterprise patterns, data flows, and security/compliance frameworks.
  2. AI Enablement and Workflow Automation
    1. Partner directly with the rapid prototyping developer to shape and refine AI-driven product features for feasibility, scalability, and quality, with primary focus on AI-augmented implementations.
    2. Develop advanced prompt engineering techniques, reusable AI patterns, and orchestration methods to accelerate implementation services. Document and standardize repeatable approaches so they can be adopted at scale.
    3. Apply generative AI to automate testing, linting, fuzz testing, and technical debt reduction. 
    4. Operationalize autonomous coding workflows (GitHub Copilot, Claude Code) with governance guardrails, review gates, and productivity metrics.
    5. Serve as the hands-on enablement lead for Implementation Services; building reference workflows, training delivery staff, and removing adoption friction so tooling produces measurable outcomes.
    6. Partner with Implementation Services leadership to document current-state data onboarding:
      1. source systems/formats (e.g., mainframe extracts, EHR exports, claims files), per-client cycle time, and where the pain concentrates (mapping logic, validation, testing, or all three).
  3. Security, Privacy and Compliance
    1. Evaluate and deploy PHI-safe LLM options (Claude Enterprise and/or local models), aligning handling with HITRUST r2 controls and HIPAA/HITECH obligations.
    2. Design and enforce guardrails for secure handling of PHI and PII within AI sessions and pipelines.
  4. Adoption, Training, and Change Enablement
    1. Establish and report adoption and impact metrics, including cycle-time reduction, mapping accuracy, defect rates, and adoption rate, suitable for SLT and board-level visibility.
    2. Lead enablement activities that drive adoption across technical and delivery teams, including training, office hours, documentation, and workflow reinforcement.
  5. Production Readiness, Knowledge Sharing and Continuous Improvement
    1. Provide AI mentorship to senior development staff and Implementation Services delivery teams via pairing sessions, design reviews, and lunch-and-learn sessions.
    2. Create and collaborate on architectural blueprints, compliance/security standards, reusable frameworks, and reference implementations for AI projects.
    3. Support transition of prototypes into production-ready, enterprise-compliant solutions.

QUALIFICATIONS

Competencies:

  • Deep technical expertise in AI/LLM engineering.
  • Strong problem-solving, analytical thinking, and attention to detail.
  • Ability to translate complex AI concepts into actionable, scalable solutions.
  • Effective mentorship and knowledge-sharing abilities with senior developers.
  • Ability to influence and drive adoption across cross-functional stakeholders.

Required Education and Experience:

  • Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
  • 5+ years of progressive AI/ML engineering, including recent, hands-on LLM development and deployment work.
  • Deep understanding of LLM internals (tokenization, context windows, reasoning behaviors).
  • Experience with model fine-tuning, evaluation, and optimization.
  • Security and privacy best practices for PHI/PII data protection in AI workflows.
  • Strong skills in prompt engineering and orchestration frameworks (LangChain, vector search, semantic caching).
  • Familiarity with NLP, OCR/ML, and document processing where applicable.
  • Strong data engineering fundamentals: ETL/ELT, schema mapping, transformation, and loading at scale.
  • Healthcare data experience; working knowledge of HIPAA/HITECH, PHI handling, and HITRUSTaligned controls.
  • Practical experience with AI coding assistants (Copilot, Claude Code, or equivalent) in a governed environment.
  • Demonstrated ability to drive adoption, translating technical capability into workflows that are sustainable.
  • Practical experience using generative AI for test automation and code quality improvements.
  • Strong collaboration and communication skills to work effectively across architecture, development, and security teams.

Work Environment. Employees may work from our corporate headquarters or work from home. Employees may at times be required to travel to headquarters for meetings or company events. Remote workers will be provided with a company laptop and are responsible for maintaining access to highspeed internet.

Physical Demands. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to sit for long periods of time, stand; walk; use hands to finger, handle or feel; and reach with hands and arms. The employee is occasionally required to climb or balance; and stoop, kneel, crouch or crawl. The employee must occasionally lift and/or move up to 10 pounds and occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus.

Position Type and Expected Hours of Work. This is a full-time position, and the hours of work and days are typically Monday through Friday, 8:30 a.m. to 5 p.m. Some flexibility in hours is allowed, but the employee must be available during the “core” work hours of 9:00 a.m. to 3:30 p.m. Occasional evening and weekend work may be required as job duties demand.

Travel. Incumbent may occasionally experience some out-of-the-area and overnight travel.

Work Authorization. In compliance with Federal employment laws, MediQuant will verify the identity and employment authorization of each person hired. MediQuant participates in the Federal E-Verify program.

Security Clearance. Must be able to pass all security clearances mandated by various government contracts as well as client hospital/healthcare security requirements. Any employee working on government projects will be required to successfully pass a government background check and receive a Common Access Card (CAC). Additionally, the applicant must be a U.S. citizen and will be subject to a Public Trust security background investigation and must meet requirements to obtain a Department of Defense (DOD) network account.

AAP/EEO Statement. MediQuant, Inc. is an equal opportunity employer.

Compliance. Employees shall comply with all MediQuant policies, state and federal laws, regulations, and contractual obligations when accessing MediQuant or client Confidential Data, Confidential Information, and Information Assets.

Other Duties. Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time.

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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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