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NextGenPros Inc Linkedin · Posted 2d ago

AI/ML Engineer

Dallas, Texas, United States

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Indexed description

Job Title: AI/ML Engineer

Location: Dallas, TX

Employment Type: Long term contract

Key Responsibilities

  • Design, develop, and deploy AI/ML models and GenAI applications in production environments.
  • Build scalable ML/AI solutions using Python and modern ML frameworks.
  • Develop and integrate LLM-based applications, RAG pipelines, AI agents, and MCP-based solutions.
  • Implement Model Context Protocol (MCP) servers/tools and integrate AI agents with enterprise systems and APIs.
  • Deploy and manage AI/ML workloads on Microsoft Azure and/or AWS.
  • Containerize applications using Docker and deploy them on AKS/Kubernetes.
  • Build and maintain CI/CD pipelines for AI/ML application and model deployments.
  • Implement MLOps practices, including model versioning, automated testing, deployment, monitoring, and rollback.
  • Develop cloud-native architectures using services such as Azure ML, Azure OpenAI, AKS, Azure DevOps and/or AWS SageMaker, EKS, Bedrock, Lambda, S3.
  • Optimize AI/ML workloads for scalability, reliability, security, and cost.
  • Integrate ML models with REST APIs, microservices, databases, and enterprise applications.
  • Monitor model/application performance and troubleshoot production issues.
  • Collaborate with DevOps and Cloud teams to implement infrastructure automation and Infrastructure as Code (IaC).
  • Follow best practices for security, authentication, secrets management, logging, and observability.

Required Technical Skills

AI/ML & GenAI

  • Strong programming experience in Python.
  • Experience with Machine Learning / Deep Learning concepts and frameworks.
  • Hands-on experience with Generative AI, LLMs, Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
  • Experience with frameworks such as LangChain, LangGraph, LlamaIndex or similar.
  • Understanding of model evaluation, optimization, and production deployment.

MCP – Model Context Protocol

  • Hands-on knowledge of Model Context Protocol (MCP).
  • Experience developing or integrating MCP servers, tools, resources, and clients.
  • Ability to connect LLM/AI agents with enterprise APIs, databases, files, and external services using MCP.
  • Understanding of secure and scalable MCP-based architectures.

Cloud – Azure / AWS

Strong experience with at least one cloud platform:

Azure:

  • Azure Machine Learning
  • Azure OpenAI
  • Azure Kubernetes Service (AKS)
  • Azure DevOps
  • Azure Storage
  • Azure Functions
  • Azure Key Vault
  • Azure Monitor

AWS:

  • Amazon SageMaker
  • Amazon Bedrock
  • Amazon EKS
  • S3
  • Lambda
  • IAM
  • CloudWatch
  • API Gateway

Kubernetes / AKS

  • Hands-on experience with Kubernetes and AKS.
  • Docker containerization.
  • Kubernetes deployments, services, ingress, ConfigMaps, Secrets, and autoscaling.
  • Experience deploying and managing AI/ML workloads in Kubernetes environments.
  • Understanding of Helm and Kubernetes networking is preferred.

CI/CD & DevOps

  • Strong experience building CI/CD pipelines.
  • Experience with Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, or similar.
  • Automated build, test, security scanning, containerization, and deployment.
  • Git/GitHub/GitLab/Bitbucket.
  • Experience with Terraform, Bicep, or CloudFormation is preferred.


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