Gen AI

Cloud Analytics Technologies, LLC; Atlanta (GA); On-site; USD 150,000 - 190,000; Full time

Job summary

Cloud Analytics Technologies, LLC is seeking a Senior Engineer (Generative AI) to design, develop, and deploy scalable GenAI solutions with a focus on AWS cloud enablement. The role requires hands-on work with LLM-based applications, GenAI architectures, and modern cloud-native practices.

You will partner with cross-functional teams to deliver production-ready AI systems that meet security, reliability, and scalability standards across enterprise environments.

Qualifications

• 5+ years of experience delivering GenAI applications using LLMs and RAG architectures.
• 5+ years building intelligent pipelines with LangChain, LangGraph, or Foundry Agent Service.
• 5+ years evaluating GenAI performance, accuracy, and scalability.
• 5+ years contributing to end-to-end GenAI lifecycle: design, integration, deployment, tuning.
• 5+ years securing deployments, horizontal scaling, and operational stability.
• 5+ years implementing monitoring, logging, and observability for production GenAI workloads.
• 5+ years deploying GenAI across cloud platforms (Azure and AWS).
• 5+ years designing distributed systems for scalable AI workloads.
• 5+ years with Docker, Kubernetes, and Infrastructure as Code (Terraform/ARM/Bicep).
• 5+ years ensuring availability, performance, and security in enterprise settings.
• 5+ years coding in Python and building microservices-based architectures.
• 5+ years applying secure coding standards and proper data handling for regulated environments.
• 5+ years contributing to CI/CD pipelines, automated testing, and deployment workflows.
• 5+ years participating in code reviews and following engineering best practices.

Responsibilities

• Design, develop, and deploy GenAI solutions for enterprise use cases.
• Build production-ready GenAI systems with AWS cloud enablement.
• Collaborate with cross-functional teams to ensure scalable, secure deployments.
• Evaluate performance, accuracy, and scalability of GenAI implementations.
• Contribute to end-to-end GenAI lifecycle from design to deployment.
• Implement monitoring, logging, and observability in production workloads.

Skills

LLMs

RAG architectures

Prompt engineering

Agentic AI

LangChain

LangGraph

Foundry Agent Service

Performance evaluation

GenAI lifecycle

Lifecycle design

Integration & deployment

Performance tuning

Secure deployment

Horizontal scaling

Observability

Terraform

Docker

Kubernetes

Python

Microservices

Secure coding

Data handling

CI/CD

Automated testing

Code reviews

Best practices

Tools

Docker

Kubernetes

Terraform

ARM/Bicep

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Description

The Senior Engineer (Generative AI) is responsible for designing, developing, and deploying scalable Generative AI (GenAI) solutions within an enterprise environment, with a focus area for AWS cloud enablement. This role requires strong hands-on expertise in LLM-based applications, GenAI architectures, and modern cloud-native engineering practices. The position partners closely with cross-functional teams to build production-ready AI systems that meet enterprise standards for scalability, security, and reliability.

Basic Qualifications

• Minimum 5+ years of experience developing and implementing GenAI applications leveraging: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, Prompt engineering techniques, and Agentic AI concepts and workflows


• Minimum 5+ years of experience building intelligent pipelines using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service


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


• Minimum 5+ years of experience contributing to the end-to-end GenAI lifecycle, including: Solution design and development, Integration and deployment, and Performance tuning and optimization


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


• Minimum 5+ years of experience assisting in implementing monitoring, logging, and observability practices for production environment


• Minimum 5+ years of experience developing and deploying GenAI systems across cloud platforms (Azure and AWS)


• Minimum 5+ years of experience contributing to distributed system design for scalable AI workloads


• Minimum 5+ years of experience utilizing modern infrastructure practices: Containerization (Docker), Orchestration (Kubernetes), and Infrastructure as Code (Terraform, ARM/Bicep)


• Minimum 5+ years of experience ensuring solutions meet enterprise expectations for availability, performance, and securit


• Minimum 5+ years of experience developing scalable applications using Python and microservices-based architecture


• Minimum 5+ years of experience applying secure coding standards and proper data handling practices for enterprise, regulated environments


• Minimum 5+ years of experience contributing to CI/CD pipelines, automated testing, and deployment workflows


• Minimum 5+ years of experience participating in code reviews and adhere to engineering best practices

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.