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# Sr. Full Stack AI Engineer 181801

- **Company:** CTI, Inc.
- **Location:** Park Hills, KY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Information Engineering, Data Infrastructure, Data Stores, Decision Support Systems, Software Design Patterns, DevOps, Programming Tools, Distributed Systems, Information Retrieval, Python (Programming Language), Machine Learning, Node.Js, Productivity Software, Software Architecture, Recommender Systems, Next.js, Software Engineering, Software Systems, TypeScript, Web Applications, Google Cloud, Cloud Platform System, GitHub Copilot, ReactJS, Large Language Models, Prompt Engineering, Generative AI, Backend, Kubernetes, Enterprise Integration, Machine Learning Operations, Claude, Api Design, Google Gemini, Data Pipelines, Programming Languages
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/sr-full-stack-ai-engineer-181801-covington-ky--87fa5a6a-7d30-4476-8889-1ac50bdcb49d

## About the Role

* Bachelor's degree or equivalent experience with 5+ years of software engineering experience.
 * Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
 * Strong experience using LLMs and Generative AI technologies to solve real business challenges
 * Strong full-stack engineering background with modern languages and frameworks such as Python, TypeScript, Node.js, APIs, React, and Next.js.
 * Hands-on experience deploying and scaling applications within cloud environments such as AWS, Azure, or Google Cloud.
 * Experience with modern platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures.
 * Strong understanding of software architecture, design patterns, security, and reliability principles for enterprise-scale applications.
 * Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions.
 * Ability to collaborate effectively across engineering, data, product, and business teams while driving initiatives from concept to production.

Top 4 Areas of Expertise

 1. Backend & Full Stack Engineering (25%)
 * Strong backend engineering background (role is heavily backend-focused)
 * Hands on experience with programming languages such as Java, Node.js, Python
 * Familiarity with modern web application architectures
 * API design, development, and integration expertise

 2. AI & LLM Engineering (25%)
 * Experience leveraging Large Language Models (LLMs) to solve business problems
 * Strong understanding of prompt engineering, prompt management, and GenAI solution design
 * Experience working with GenAI developer tools such as: GitHub Copilot, Gemini, Claude
 * Familiarity with AI strategy, implementation, and scaling AI-driven solutions

 3. Data Platform Engineering (25%)
 * Strong data engineering experience
 * Experience with data pipelines, data stores, orchestration frameworks, and distributed systems
 * Understanding of machine learning workflows and AI-enabled applications
 * Experience deploying and scaling AI/ML solutions in production environments

 4. Cloud Architecture, Scale & Security (25%)
 * Cloud-native development experience
 * Kubernetes and containerized application deployment
 * Experience with deployment patterns and scalable system design
 * Understanding of secure, enterprise-grade architecture

Ultimately, I need a hands-on Senior AI Engineer who combines GenAI/LLM experience, strong software and data engineering fundamentals, and cloud platform expertise to design, build, and deploy AI solutions that solve real business challenges, enhance advisor efficiency, and automate key processes at scale.

## Description

Representative initiatives may include developing AI-powered capabilities that improve advisor effectiveness and client engagement, such as:

 * Automated meeting preparation and research
 * Intelligent call summarization and insight generation
 * Automated follow-up and workflow orchestration
 * Knowledge retrieval and recommendation systems
 * AI-assisted decision support and productivity tools
 * Workflow automation leveraging enterprise data sources and communication channels