Job Type: Contract
Job Category: IT
Job Description
Job Title: MLOps Architect (AWS CDK Focus)
Job Summary:
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.
- Knowledge domain-driven data architecture.
- 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.
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