Gen AI Senior Engineer

Location: Charlotte, NC / Atlanta, GA / Minneapolis, MN / Irving, TX / Chicago, IL / Cincinnati, OH
Work Arrangement: Onsite – 5 Days a Week

Candidates local or nearby to any USB Hub location will be required to attend a face-to-face client interview.

Job Overview

We are seeking an experienced Senior Generative AI Engineer to design, develop, and deploy scalable Generative AI (GenAI) solutions within an enterprise environment, with a focus on AWS cloud enablement.

The ideal candidate will have strong hands-on expertise in Large Language Model (LLM)-based applications, GenAI architectures, Agentic AI workflows, and modern cloud-native engineering practices. This role will collaborate with cross-functional teams to build production-ready AI systems that meet enterprise standards for scalability, security, reliability, and performance.

Key Responsibilities

• Design, develop, and implement enterprise-grade Generative AI applications using LLMs, RAG architectures, prompt engineering, and Agentic AI concepts.

• Build intelligent AI pipelines and workflows using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service.

• Evaluate and optimize GenAI solutions for performance, accuracy, scalability, and reliability.

• Contribute to the end-to-end GenAI lifecycle, including solution design, development, integration, deployment, performance tuning, and optimization.

• Support secure deployment, horizontal scaling, and operational stability of GenAI workloads.

• Implement monitoring, logging, and observability practices for production AI environments.

• Develop and deploy GenAI systems across cloud platforms, particularly AWS and Azure.

• Contribute to distributed system design for scalable AI workloads.

• Implement containerization, orchestration, and Infrastructure as Code practices.

• Ensure enterprise solutions meet availability, performance, security, and reliability requirements.

• Develop scalable applications using Python and microservices-based architecture.

• Apply secure coding standards and appropriate data-handling practices for enterprise and regulated environments.

• Contribute to CI/CD pipelines, automated testing, and deployment workflows.

• Participate in code reviews and follow software engineering best practices.

Required Qualifications

• 5+ years of experience developing and implementing GenAI applications leveraging:

  • Large Language Models (LLMs)

  • Retrieval-Augmented Generation (RAG)

  • Prompt Engineering

  • Agentic AI concepts and workflows

• 5+ years of experience building intelligent pipelines using:

  • LangChain

  • LangGraph

  • Microsoft Foundry Agent Service

• 5+ years of experience evaluating GenAI solution performance, accuracy, and scalability.

• 5+ years of experience across the end-to-end GenAI lifecycle, including solution design, development, integration, deployment, and optimization.

• 5+ years of experience supporting secure deployment, horizontal scaling, and operational stability of GenAI workloads.

• 5+ years of experience with monitoring, logging, and observability practices.

• 5+ years of experience developing and deploying GenAI systems across cloud platforms, including AWS and Azure.

• 5+ years of experience with distributed system design for scalable AI workloads.

• 5+ years of experience with modern infrastructure practices:

  • Docker

  • Kubernetes

  • Terraform

  • ARM/Bicep

• 5+ years of experience developing scalable applications using Python and microservices architecture.

• 5+ years of experience applying secure coding standards and data-handling practices in enterprise or regulated environments.

• 5+ years of experience with CI/CD pipelines, automated testing, and deployment workflows.

• Experience participating in code reviews and following engineering best practices.

Education

Bachelor’s degree in Computer Science or equivalent work experience.

Work Location & Interview Requirements

• This is an onsite position requiring 5 days per week in a client office.

• Candidates must be located locally or within commuting distance of one of the following locations:

  • Charlotte, NC

  • Atlanta, GA

  • Minneapolis, MN

  • Irving, TX

  • Chicago, IL

  • Cincinnati, OH

Additional Information

Candidates should have strong hands-on GenAI engineering experience and the ability to build, deploy, and support secure, scalable, production-ready AI solutions in enterprise cloud environments.

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