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 contractposition 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.

1. AI Solution Design and Implementation
2. Machine Learning and Data Science Expertise
3. 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