Principal AWS Data Platform, ML Ops Architect

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Architect and develop the Shared Platform.

• Establish the target AWS architecture for shared data, document processing, search, analytics, and AI functionalities.

• Create the canonical data model, ingestion and processing pipelines, storage patterns, APIs, event contracts, and serving layers.

• Construct a reusable platform that supports multiple products and projects with essential shared capabilities while establishing repeatable implementation patterns for engineering teams.

• Formulate an incremental migration and adoption strategy to transition existing solutions onto the shared platform.

• Detect duplicated pipelines, services, infrastructure, and technical patterns across various projects.

• Ascertain which capabilities should be incorporated as shared platform services and which should remain project-specific.

• Define the Data and MLOps Architecture.

• Design the AWS-based pathway from data science deliverables to production by establishing architecture for model packaging, deployment, serving, registry, monitoring, drift detection, and retraining workflows.

• Set onboarding standards for new data products, models, search applications, and AI-enabled services.

• Design platform capabilities that support search indexes, embeddings, vector retrieval, RAG, and model evaluation.

• Provide Technical Design Authority.

• Lead architecture and design reviews prior to significant development initiatives.

• Establish reference architectures, approved patterns, architecture decision records, and engineering standards.

• Mandate teams to utilize shared platform capabilities where applicable and assess justified exceptions.

• Guarantee that platform designs fulfill performance, scalability, reliability, security, auditability, disaster recovery, and cost criteria.

• Offer technical leadership and mentoring across data engineering, data science, software engineering, and platform teams.

• Collaborate with product and engineering leaders to build a cross-project platform roadmap.

⛳️ Requirements

• Current AWS Certifications (Solutions Architect, Data Engineer, or Machine Learning).

• Extensive experience in designing and constructing enterprise data platforms or AI/ML platforms on AWS.

• Proven experience in creating shared platform capabilities embraced by multiple products, projects, or business units.

• Experience in consolidating separate production data systems through incremental migration and adoption.

• Strong practical AWS architecture experience essential for Data, AI, ML Engineering, including S3, DynamoDB, Lambda, ECS, Fargate, AWS Batch, Step Functions, SQS, SNS, EventBridge, OpenSearch Service, Glue, Athena, SageMaker, IAM, KMS, and CloudWatch.

• In-depth experience in data engineering, distributed systems, event-driven architecture, APIs, data modeling, metadata, lineage, governance, and access control.

• Extensive MLOps architecture experience, including model deployment, serving, registries, monitoring, drift detection, and retraining workflows.

• Familiarity with designing foundations for search, vector retrieval, embedding, or RAG data.

• Experience with infrastructure as code using AWS CDK, Terraform, or CloudFormation.

• Knowledge of multi-account AWS environments, private networking, and AWS Well-Architected principles.

• Ability and willingness to write production code and develop initial critical platform components.

• Experience in influencing senior engineers and enforcing architectural decisions across teams without direct management authority.

• Strong technical communication and decision-making abilities.

• Must be authorized to work in the United States and have resided in the US for three or more consecutive years.

• Must be willing and able to obtain a Public Trust Clearance.

🏝️ Benefits

• Health Insurance - 100% employer-paid premiums – ICA covers the entire cost of one of three offered medical plans.

• Dental Insurance.

• Vision Insurance.

• Health Spending Account.

• Flexible Spending Account.

• Life and Disability Insurance.

• 401(k) plan with company match.

• Paid Time Off (Vacation, Sick Leave, and Holidays).

• Education and Professional Development Assistance.

• Remote work from anywhere within the continental United States.