AI Implementation Architect
4 weeks ago
Job Title: AI Implementation Architect
Location: Memphis, TN (Preferred) or Remote
Duration: 18 Months + Extensions (Long-term contract.)
Start Date: ASAP
Number of Openings: 1
Top Skills in order of preference.
- AI Solution Design and Implementation
- Machine Learning and Data Science Expertise
- AI Architecture and Pipeline Planning
ESSENTIAL JOB FUNCTIONS
- Design and build data and AI infrastructure systems including model selection and versioning, indexing, feedback capture, monitoring, and performance.
- Integration: Implement AI solutions that integrate seamlessly with existing business systems and enhance functionality. Work with systems and application owners to design complementary AI solutions.
- Collaboration: Work with data scientists, enterprise architects, and stakeholders to develop and deploy AI models based on use cases and value.
- Operations: Ensure scalability, reliability, and security of AI and data orchestration systems. Design systems to produce ethical, un-biased output.
- 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.
REQUIREMENTS
- 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.
- Strong ability to translate use case and business domain functions to production applications o Proficiency in programming languages (Python, Java) and related AI/ML frameworks (ex. LangChain, TensorFlow, PyTorch).
- Experience with prompt flows, prompt engineering best practices, and AI patterns (ex. Retrieval Augmented Generation (RAG)) o Development and production deployment experience with data products on public cloud platforms (Azure and AWS preferred) o Knowledge of vector databases, search indexes, and embeddings.
- Experience with fine-tuning (PEFT) is a plus o Experience with API architecture and design is a plus.
- Education: Bachelor's degree in Computer Science, Engineering, or a related field.
- Certifications: Relevant certifications in AI, data engineering, or cloud computing are a plus.
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