[Hiring] Principal AWS Data Platform & ML Ops Architect @ICA.ai

Role Description

We are 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. Your mandate will be to establish a unified AWS-native platform, including shared data models, pipelines, services, and serving layers that can support document intelligence, semantic and multimodal search, RAG applications, data science projects, dashboards, and analytics. You will define the technical direction and build the platform capabilities through hands-on development and by guiding other Data Engineers.

Key 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.

Qualifications

• 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.

Preferred Qualifications

• 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.

Benefits

• Health Insurance - 100% employer-paid premiums; ICA covers the full 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

Location & Telework

This is a remote position following Eastern Standard Time (EST). Candidates residing in the DMV area preferred.

Additional Information

ICA is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender, gender identity or expression, national origin, genetics, disability status, protected veteran status, age, or any other characteristic protected by state, federal or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.