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AI Implementation Engineer

Job in Memphis, Shelby County, Tennessee, 38103, USA
Listing for: Syntricate Technologies
Full Time position
Listed on 2026-07-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below

AI Implementation Engineer

Please take a moment to review the job description below. If you are interested in applying, please reply so we can talk about it more. This is a contract position and we are offering payment options of W2/1099 & C2C per hour. The interview process will be initiated as soon as possible. We are excited to hear back from you.

Job Description:

Role

AI Implementation Engineer

Duration

Long-Term Contract

Location

Memphis, TN – 100% Remote

Top Skills in Order of Preference
  • AI Solution Design and Implementation
  • Machine Learning and Data Science Expertise
  • AI Architecture and Pipeline Planning
  • Qualifications / Experience
    • Proven experience as a Data Engineer, AI Engineer, or similar role, with a focus on production, customer facing implementation of data orchestration and AI technologies.
    • Proficiency in programming languages (Python, Java), familiarity with related AI/ML frameworks (ex. Lang Chain, Tensor Flow, PyTorch).
    • Experience with prompt flows, prompt engineering best practices, and AI patterns (ex. Retrieval Augmented Generation (RAG))
    • Development and production deployment experience with data products on public cloud platforms (Azure and AWS preferred)
    • Strong development practices including source control, testing methodologies, and, preferably, Dev Ops or CI/CD processes and tooling
    • Familiarity with vector databases, search indexes, and embeddings
    • Experience with application and API development practices
    Essential Job Functions
    • Collaboration:

      Work with AI architect, infrastructure, and other engineers to develop and deploy AI models based on jointly created designs.
    • Operations:
      Ensure scalability, reliability, and security of AI and data orchestration systems. Design systems to produce ethical, un-biased output.
    • Support:
      Provide SME level support, document, and guidance for implemented AI processes.
    • Governance and Improvement:
      Monitor and improve AI systems based on performance metrics and user feedback. Implement governance and observation methodologies to provide transparency to model operations.
    • Data Preparation:
      Design and implement processes to improve data quality, synthesize data, produce training sets, and generally prepare data for AI usage.
    Education
    • Bachelor's degree in Computer Science, Engineering, or a related field
    Certifications
    • Relevant certifications in AI, data engineering, or cloud computing
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