Principal Full Stack AI Engineer

You will work closely with engineering, architecture, data science, product, and business teams to identify high-value use cases and build secure, scalable solutions that improve productivity, automate workflows, and enhance user experiences., * Design and develop scalable, production-grade AI and software solutions.

• Architect and implement LLM and Generative AI applications for enterprise use cases.
• Apply prompt engineering, LLM integration, RAG, knowledge retrieval, and AI-enabled automation techniques.
• Develop robust backend services, APIs, and distributed applications using modern programming languages.
• Build full-stack applications using modern frontend and backend frameworks when required.
• Design and implement data pipelines, data services, data stores, and orchestration workflows supporting AI applications.
• Deploy and scale applications using cloud-native technologies.
• Build and maintain containerized applications using Docker and Kubernetes.
• Apply Infrastructure-as-Code, CI/CD, DevOps, security, reliability, and observability best practices.
• Partner with architects, product managers, data scientists, engineers, and business stakeholders to translate business problems into technical solutions.
• Establish engineering best practices and contribute to technical direction for a new AI engineering organization.
• Drive initiatives from proof of concept through production deployment and enterprise scale.

This is a greenfield opportunity for a senior hands-on engineer who can work across Generative AI/LLMs, backend and full-stack development, data engineering, cloud architecture, and platform engineering.

The ideal candidate will have a strong software engineering foundation and proven experience taking AI-powered solutions from concept and architecture through production and scale., * Strong hands-on experience with Large Language Models (LLMs) and Generative AI.

• Experience designing and implementing production GenAI solutions.
• Strong understanding of prompt engineering and prompt management.
• Experience with RAG, knowledge retrieval, AI agents, or similar LLM-based architectures.
• Experience with AI developer tools such as GitHub Copilot, Gemini, Claude, or comparable tools.
• Understanding of AI strategy, implementation, evaluation, and scaling.

<>2. Backend & Full Stack Engineering - 25%

• Strong backend software engineering experience.
• Hands-on experience with Python, Java, Node.js, or similar languages.
• Strong experience designing and developing REST APIs and distributed services.
• Experience with modern full-stack architectures.
• Experience with TypeScript, React, and/or Next.js is highly desirable.
• Strong understanding of software architecture and design patterns.

<>3. Data Platform Engineering - 25%

• Strong experience with data engineering and data platforms.
• Experience designing data pipelines, data stores, and orchestration frameworks.
• Understanding of distributed systems and scalable data architectures.
• Experience supporting machine learning and AI-enabled applications.
• Experience deploying and scaling AI/ML solutions in production environments.

<>4. Cloud Architecture, Scale & Security - 25%

• Strong cloud-native development experience with AWS, Azure, or Google Cloud.
• Hands-on experience with Kubernetes and containerized applications.
• Experience with Infrastructure-as-Code and modern DevOps practices.
• Strong understanding of scalable system design.
• Knowledge of enterprise security, reliability, performance, and observability principles.
• Experience designing highly available and production-grade cloud applications., * Bachelor’s degree or equivalent practical experience with 8+ years of software engineering experience, or Master’s degree with 6+ years of experience.
• Proven experience designing and delivering scalable, production-grade software systems.
• Strong hands-on experience with Generative AI and LLM technologies.
• Strong software engineering and backend development background.
• Experience with cloud platforms and cloud-native application development.
• Experience with containers, Kubernetes, and modern DevOps practices.
• Strong communication, problem-solving, and technical leadership skills.
• Ability to work effectively with technical and non-technical stakeholders., * Experience building enterprise GenAI platforms or applications.
• Experience with RAG, vector databases, embeddings, AI agents, or LLM orchestration frameworks.
• Experience with financial services, wealth management, banking, or other highly regulated environments.
• Experience leading greenfield engineering initiatives.
• Experience establishing engineering standards and best practices for AI applications.

Work Arrangement

This is an onsite position in Covington, KY. Candidates should be local and able to commute to the work location.

Candidates must be willing to work onsite and should be located within a reasonable commuting distance.