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# Sr. AI Engineer

- **Company:** Randstad
- **Location:** Covington, KY, United States
- **Experience:** Expert
- **Salary:** $164,320.0 - $166,400.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Cloud Engineering, Information Engineering, Decision Support Systems, Software Design Patterns, DevOps, Distributed Systems, Python (Programming Language), Knowledge-Based Systems, Node.Js, Productivity Software, Software Architecture, Recommender Systems, Next.js, Search Technologies, Software Engineering, Software Systems, TypeScript, Google Cloud, Cloud Platform System, ReactJS, Large Language Models, Multi-Agent Systems, Generative AI, Kubernetes
- **Published:** September 4, 2026
- **Apply:** https://www.dice.com/job-detail/63d33ec5-1b22-43a8-891c-6a9e894aecbf

## About the Role

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 optimally across engineering, data, product, and business teams while driving initiatives from concept to production., 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.

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.

skills:

AWS,APIs,AI,AI engineering,AI solutions,artificial intelligence,AI capabilities,AI applications,cloud technologies,cloud-native architectures,cloud environments,cloud platform,decision support,DevOps practices,distributed systems,Retrieval-Augmented Generation (RAG),Google Cloud,data engineering,knowledge systems,orchestration platforms,Kubernetes,large language models,LLMs,LLM,Azure,agent frameworks,Next.js,Node.js,productivity tools,Python,React,recommendation systems,semantic search,AI-powered applications,software architecture,design patterns,software engineering,software solutions,TypeScript,passion,problem-solving skills,reliability,administrative,advanced analytics,automation,Automated,automate,brand,business needs,client experience,client engagement,communication channels,full-stack engineering,Infrastructure,innovative,innovative solutions,Investments,platform engineering,Use Cases,security,vector databases,workflows,Workflow automation

## Description

As an early member of this organization, you will play a key role in designing, building, and delivering AI-powered solutions from concept through production. This position offers the opportunity to collaborate closely with business partners, product teams, architects, data scientists, and fellow engineers to identify high-value opportunities and develop secure, scalable, enterprise-grade AI capabilities that drive important business outcomes., This role is ideal for a hands-on Sr. AI Engineer who thrives at the intersection of AI, software engineering, data engineering, and cloud technologies. Successful candidates will possess strong technical expertise and a passion for building innovative solutions, partnering with cross-functional teams to translate business needs into practical AI applications. The ideal individual enjoys solving complex technical challenges, developing production-ready systems, and working towards the evolution of modern AI platforms and capabilities.


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