AI - Data Engineer

Creative Artists Agency•Nashville, TN

16h•Hybrid

About The Position

The AI Engineer is a member of a highly motivated CAA Tech team responsible for accelerating the creation of opportunity through the strategic use of data. In this role, you will design and build intelligent systems that transform complex information into structured knowledge and actionable insights using modern AI, machine learning, and generative approaches to solve complex business problems. You will operate across the full lifecycle, from experimentation and evaluation to deployment and optimization, developing solutions that ingest, interpret, and reason over large volumes of data. The ideal candidate combines strong software engineering fundamentals with hands-on experience building applied AI systems that operate reliably in production environments and deliver measurable business impact.

Requirements

Minimum of 6 years building AI, Machine Learning and NLP solutions.
Minimum 3 years building applied AI/LLM and generative systems in production environments.
Bachelor’s degree in a relevant field such Mathematics, Science, Engineering, or Computer Science.
Strong programming skills in Python and experience building data and AI pipelines.
Experience with information retrieval, semantic search, or knowledge-driven systems.
Experience with relational, non-relational and semantic data stores.
Strong software engineering fundamentals (APIs, system design, testing, version control).
Excellent analytical and problem-solving skills.
Demonstrated initiative and ownership of tasks and projects.
Ability to prioritize, coordinate, and complete tasks to meet deadlines.
Ability to work effectively both independently and in team environments.
Ability to present complex problems in simple terms.

Nice To Haves

Master’s Degree in relevant discipline preferred.
Experience with Natural Language Processing methods and applications preferred.

Responsibilities

Design and implement end-to-end AI workflows for complex data interpretation, knowledge extraction, and reasoning.
Build systems that convert unstructured content into structured representations.
Develop and optimize retrieval approaches that combine semantic and lexical search techniques.
Prototype, evaluate approaches, test feasibility, and productionize generative AI solutions for real-world use cases.
Partner with engineering teams to develop technology infrastructure.
Optimize systems for latency, cost, and throughput.
Design and implement evaluation approaches to assess performance, relevance, and effectiveness of AI solutions.
Apply techniques to improve consistency, accuracy, and trustworthiness of outputs.
Implement methods for scoring, explainability, and ongoing quality assurance.
Monitor deployed solutions and data pipelines for performance, stability, and data quality over time.
Identify data sources that can be useful to answer business questions.
Perform experiments on ingested data to evaluate quality and integrity.
Build data pipelines for ongoing data extraction.
Work closely with cross-functional teams to align data science initiatives with business priorities.
Partner with leadership to identify and prioritize high-impact opportunities for data science applications.
Present insights and recommendations through clear visualizations tailored for audiences across different roles and expertise levels.