MLOps Architect (AWS CDK Focus)

AceStack; Atlanta (GA); On-site; USD 65,000 - 110,000; Part time

Job summary

A leading company seeks a skilled MLOps Architect to design and implement cloud-native data governance and MLOps frameworks. The ideal candidate will leverage AWS CDK to build scalable and automated data and ML platforms, collaborate across teams to ensure compliance and security, and enhance data accessibility through effective governance solutions.

Qualifications

• 7+ years of cloud architecture or data engineering experience.
• Strong hands-on experience with AWS CDK in Typescript or Python.
• Deep knowledge of cloud services like AWS DataZone and SageMaker.

Responsibilities

• Architect and deploy AWS DataZone for data governance.
• Build CI/CD-enabled MLOps pipelines for ML lifecycle management.
• Collaborate with diverse teams to design solutions.

Skills

AWS CDK

Cloud Architecture

Automation

Data Governance

Problem Solving

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Docker

SageMaker

Lambda

EKS

Job description

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Location: Atlanta, GA or Minneapolis, MN

Job Description:

We are looking for a highly skilled MLOps Architect to design, implement, and oversee modern cloud-native data governance and machine learning operations (MLOps) frameworks with deep expertise in designing scalable, secure, and automated cloud-native data and ML platforms using AWS CDK. The successful candidate will be responsible for architecting & implementing robust data governance using AWS DataZone, and building MLOps pipelines leveraging services like SageMaker, Step Functions, and CodePipeline, all provisioned and maintained through CDK-based infrastructure-as-code.

This role requires strong cloud-native architectural thinking, automation-first mindset, and hands-on experience with CDK in either Typescript or Python.

Key Responsibilities:

• Architect and deploy AWS DataZone for enterprise-wide data discovery, cataloging, and governance using AWS CDK.

• Design and build CI/CD-enabled MLOps pipelines to manage the end-to-end ML lifecycle: data prep, training, model deployment, monitoring, and retraining.

• Use AWS CDK to manage infrastructure-as-code across data and ML workflows (e.g., SageMaker, Lambda, S3, Glue, DataZone, Step Functions).

• Integrate DataZone with Lake Formation, Glue Data Catalog, and Redshift for centralized governance and access control.

• Define policies and automation for data access requests, lineage, and classification using DataZone and IAM roles.

• Ensure security, compliance, and auditability across all components using least-privilege principles and automation.

• Collaborate with Data Engineers, MLOps Engineers, Data Scientists, and Security teams to design end-to-end solutions.

• Drive adoption of reusable CDK constructs/modules for consistent deployment and governance of data and ML services.

Required Skills and Experience :

• 7+ years in cloud architecture, DevOps, or data engineering roles.

• Overall 10-12+ years of exp reqd.

• Strong hands-on experience with AWS CDK in Typescript or Python (required).

• Deep knowledge of AWS DataZone, SageMaker, Glue, Lake Formation, IAM, Step Functions, CodePipeline, and CloudWatch.

• Experience architecting MLOps pipelines and automating deployments in AWS.

• Proficient in containerization using Docker, ECS, or EKS.

• Working knowledge of data governance, metadata management, and data security/compliance frameworks (e.g., HIPAA, GDPR).

• Strong programming skills in Python and scripting tools for automation.

• Understanding of data privacy, compliance, and enterprise governance frameworks.

• Excellent communication and stakeholder management skills.

• High Consulting skills reqd that takes key stakeholders in confidence and provide them day to day solutions on overall solution that includes Data Zone, MLOps and CDK.

• Model Monitoring and Evaluation: Experience with model performance monitoring, drift detection, and explainability.

Preferred Qualifications:

• AWS Certifications (Solutions Architect Professional, DevOps Engineer, or Machine Learning Specialty).

• Experience deploying enterprise-scale data platforms using CDK and reusable infrastructure modules.

• Familiarity with observability/monitoring tools for ML and data pipelines.

• Previous experience with versioned deployment strategies (Blue/Green, Canary) for ML models.

• Exposure to data observability tools and model monitoring frameworks.

• Communication and Collaboration: Ability to communicate effectively with diverse teams.

• Problem-Solving: Strong analytical and problem-solving skills.

• Leadership: Ability to lead and guide technical teams

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Software Development

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