Principal AWS Data Platform & ML Ops Architect (Remote, Continental United States)

ICA.ai•Arlington, VA

7d•Remote

About The Position

International Consulting Associates, Inc. (ICA, Inc.) is seeking a hands-on Principal AWS Data Platform & MLOps Architect to design and build a shared data and AI platform supporting multiple products and projects. The role involves establishing a unified AWS-native platform with shared data models, pipelines, services, and serving layers to support various AI and data initiatives. The architect will define the technical direction and build platform capabilities through hands-on development and by guiding other Data Engineers.

Requirements

Active AWS Certifications (Solutions Architect, Data Engineer or Machine Learning)
Extensive experience designing and building enterprise data platforms or AI/ML platforms on AWS.
Demonstrated experience creating shared platform capabilities adopted by multiple products, projects, or business units.
Experience consolidating separate production data systems through incremental migration and adoption.
Strong hands-on AWS architecture experience key for Data, AI, ML Engineering including S3, DynamoDB, Lambda, ECS, Fargate, or AWS Batch, Step Functions, SQS, SNS, and EventBridge, OpenSearch Service, Glue and Athena, SageMaker, IAM, KMS, and CloudWatch
Strong experience with data engineering, distributed systems, event-driven architecture, APIs, data modeling, metadata, lineage, governance, and access control.
Strong MLOps architecture experience, including model deployment, serving, registries, monitoring, drift detection, and retraining workflows.
Experience designing search, vector retrieval, embedding, or RAG data foundations.
Experience with infrastructure as code using AWS CDK, Terraform, or CloudFormation.
Experience with multi-account AWS environments, private networking, and AWS Well-Architected principles.
Ability and willingness to write production code and build initial critical platform components.
Experience influencing senior engineers and enforcing architecture decisions across teams without direct management authority.
Strong technical communication and decision-making skills.
Must be authorized to work in the United States and have lived in the US for 3 or more consecutive years.
Must be able and willing to obtain a Public Trust Clearance

Nice To Haves

Experience with document intelligence, OCR, multimodal search, data lake or lakehouse platforms, or generative AI systems.
Experience with Amazon Textract, Amazon Bedrock, SageMaker, OpenSearch vector capabilities, or AWS Lake Formation.
Experience working with regulated, sensitive, or access-controlled data.
Familiarity with audit, data provenance, evidence retention, tenant isolation, and model-governance requirements.
Experience establishing shared platform practices in consulting, professional-services, or multi-client environments.
Experience with AWS Organizations, Control Tower, disaster recovery, and cloud cost optimization.

Responsibilities

Architect and Build the Shared Platform: Define the target AWS architecture for shared data, document-processing, search, analytics, and AI capabilities. Design the canonical data model, ingestion and processing pipelines, storage patterns, APIs, event contracts, and serving layers. Build a reusable platform serving multiple products and projects with critical shared capabilities and establish repeatable implementation patterns for engineering teams. Develop an incremental migration and adoption strategy for bringing existing solutions onto the shared platform. Identify duplicated pipelines, services, infrastructure, and technical patterns across projects. Determine which capabilities should become shared platform services and which should remain project-specific.
Define the Data and MLOps Architecture: Design the AWS-based path from data science deliverables to production by establishing architecture for model packaging, deployment, serving, registry, monitoring, drift detection, and retraining workflows. Define onboarding standards for new data products, models, search applications, and AI-enabled services. Design platform capabilities supporting search indexes, embeddings, vector retrieval, RAG, and model evaluation.
Provide Technical Design Authority: Lead architecture and design reviews before significant development begins. Establish reference architectures, approved patterns, architecture decision records, and engineering standards. Require teams to use shared platform capabilities where appropriate and evaluate justified exceptions. Ensure platform designs meet performance, scalability, reliability, security, auditability, disaster-recovery, and cost requirements. Provide technical leadership and mentoring across data engineering, data science, software engineering, and platform teams. Partner with product and engineering leaders on a cross-project platform roadmap.