AI/ML Architect, SME

LouisianaNOW.Jobs

. Define, document, and maintain a scalable, modular AI/ML architecture aligned with enterprise cloud strategy and CMM Program requirements .

Posted 10/14/2026full-timeRemote • Louisiana • United StatesSeniorLead💰 $170,144 - $212,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and deploying scalable AI/ML solutions in cloud environments, with a strong focus on MLOps best practices and compliance with federal standards. Proficient in managing AI/ML lifecycle, ensuring performance, security, and responsible AI principles.

Highest-signal resume keywords

AI/ML Architecture DesignMLOps Best PracticesCloud Environment DeploymentPython ProgrammingFederal Compliance Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML Pipeline DevelopmentModel Training and DeploymentFeature EngineeringModel Validation and OptimizationInfrastructure-as-CodeDocker ContainerizationKubernetes OrchestrationTensorFlowPyTorchAmazon SageMaker

Soft Skills

Technical LeadershipStrategic DirectionCollaboration

Tools & Technologies

MLflowKubeflowTerraformAzure Machine LearningGoogle Cloud Vertex AI

Certifications & Qualifications

AWS Certified Machine Learning Engineer – AssociateMicrosoft Certified: Azure AI Apps and Agents Developer AssociateGoogle Cloud Professional Machine Learning Engineer

Industry Keywords

CMM ProgramMulti-Tenant SystemsCloud-Native ArchitectureFederal Data GovernanceNIST 800-53

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDistributed SystemsDockerKerasKubernetesPythonPyTorchScikit-LearnTensorflowTerraform

About the role

Key responsibilities & impact

Define, document, and maintain a scalable, modular AI/ML architecture aligned with enterprise cloud strategy and CMM Program requirements
Architect and implement end-to-end AI/ML pipelines covering data ingestion, feature engineering, model training, deployment, monitoring, and retraining
Integrate MLOps best practices for continuous integration, delivery, and machine learning model lifecycle management
Ensure multi-tenant and multi-region AI/ML workloads are elastic, highly available, and cost-efficient
Use Infrastructure-as-Code tools to provision and manage cloud-based AI/ML infrastructure according to federal compliance and security standards
Design and support reusable, secure, performant AI/ML services and APIs for enterprise applications
Conduct model validation and optimization in cloud environments while ensuring responsible AI, fairness, and transparency
Maintain AI/ML architecture documentation and update artifacts per sprint cycles or as changes occur
Support inclusion of AI/ML metrics, resource utilization, and performance KPIs in technical dashboards and reports
Guide teams in selecting and securely integrating third-party ML tools, frameworks, or SaaS offerings
Provide technical leadership, strategic direction, and AI/ML architecture tool recommendations for the CMM Program

Requirements

What you’ll need

BA/BS or equivalent required; Master of Arts or Science in a related field preferred
15+ years of related experience required
At least 5+ years of recent, demonstrable, hands-on experience architecting and deploying AI/ML workflows in cloud environments
Experience may be considered in lieu of degree: HS with 19+ years, AA/AS with 17+ years, BA/BS with 15+ years, MA/MS with 13+ years, or Doctorate/Ph.D. with 12+ years
Experience with Amazon SageMaker AI, Azure Machine Learning, and/or Google Cloud Vertex AI
Hands-on experience with TensorFlow, PyTorch, scikit-learn, XGBoost, or Keras
Strong Python programming skills
Experience with Docker containerization and Kubernetes orchestration
Experience with MLflow, Kubeflow, TFX, Airflow, and CI/CD integration for model deployment
Familiarity with federal data governance, security, and privacy standards, including JISF, NIST 800-53, and FedRAMP
Proficiency with Terraform, CDK, or CloudFormation
Experience with multi-tenant distributed systems and cloud-native architecture patterns
Must be able to pass a background check to obtain a position of Public Trust
Must be a US Person: Green Card Holder, US Permanent Resident Alien, Refugee, Asylee, or US Citizen
Preferred but not required: AWS Certified Machine Learning Engineer – Associate; AWS Certified Machine Learning – Specialty; Microsoft Certified: Azure AI Apps and Agents Developer Associate; Microsoft Certified: Machine Learning Operations Engineer Associate; Google Cloud Professional Machine Learning Engineer

Benefits

Comp & perks

Comprehensive medical plan options, including plans with Health Savings Accounts
Dental plan options
Vision plan
401(k) plan with pre-tax and post-tax contributions and company match
Full flex work weeks where possible
Vacation, sick, personal, holiday, paid parental, military, bereavement, and jury duty leave
Typically 15 days of paid leave per calendar year
10 paid holidays per year
Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees
Short- and long-term disability benefits
Life insurance
Accidental death and dismemberment insurance
Personal accident insurance
Critical illness insurance
Business travel and accident insurance
AI-powered career tool identifying career steps and learning opportunities
Internal mobility team supporting career goals
Wellness packages
Competitive pay
Military-friendly workplace
Growth and professional development opportunities