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% RemoteTOP 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. LangChain, TensorFlow, 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, DevOps 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