Principal AI Engineer 181797

CTI Consulting•Covington, KY

39d

About The Position

This role focuses on developing AI-powered capabilities to enhance advisor effectiveness and client engagement. Key initiatives include automated meeting preparation, intelligent call summarization, automated follow-ups, knowledge retrieval systems, AI-assisted decision support, and workflow automation using enterprise data and communication channels.

Requirements

Bachelor's degree or equivalent experience with 8+ years of software engineering experience, or a Master's degree with 6+ years of experience.
Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
Deep expertise building AI-powered applications utilizing large language models (LLMs), agent frameworks, and orchestration platforms (e.g., OpenAI, Claude, Bedrock, LangChain, LangGraph).
Experience developing Retrieval-Augmented Generation (RAG) solutions, semantic search capabilities, and enterprise knowledge systems leveraging vector databases and retrieval frameworks.
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.

Responsibilities

Developing AI-powered capabilities that improve advisor effectiveness and client engagement.
Implementing automated meeting preparation and research.
Creating intelligent call summarization and insight generation tools.
Automating follow-up processes and workflow orchestration.
Building knowledge retrieval and recommendation systems.
Developing AI-assisted decision support and productivity tools.
Automating workflows leveraging enterprise data sources and communication channels.
Designing and delivering scalable, production-grade software solutions and distributed systems.
Building AI-powered applications utilizing large language models (LLMs), agent frameworks, and orchestration platforms.
Developing Retrieval-Augmented Generation (RAG) solutions, semantic search capabilities, and enterprise knowledge systems.
Deploying and scaling applications within cloud environments.
Applying modern platform engineering and DevOps practices.
Ensuring strong software architecture, design patterns, security, and reliability for enterprise-scale applications.
Collaborating effectively across engineering, data, product, and business teams.
Driving initiatives from concept to production.
Identifying business problems and delivering production AI solutions that improve advisor productivity, automate workflows, and create measurable business outcomes.