Senior Cloud & Data Platform Architect - AWS, Microservices

Machine Learning Technologies, LLC; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Machine Learning Technologies, LLC seeks a senior Cloud Architect to lead the end-to-end architecture for high-traffic, customer-facing web applications. You will design scalable microservices-based and event-driven solutions using Node.js, REST, and GraphQL, and define relational and non-relational data models optimized for high-volume OLTP workloads on PostgreSQL.

You will also create architecture blueprints covering application layers, data flows, integration, observability, and deployment

Qualifications

• Extensive experience leading architecture for high-traffic, customer-facing web apps.
• Demonstrated ability to design scalable microservices and event-driven systems.
• Strong data modeling skills for OLTP workloads and relational/non-relational stores.

Responsibilities

• Lead end-to-end architecture for large-scale web applications.
• Define and enforce architecture blueprints across teams and projects.
• Collaborate with product, UX, DevOps, and QA to ensure cohesive delivery.
• Mentor engineers and junior architects on cloud-native best practices.
• Drive security, observability, and cost-optimized cloud design.

Skills

Architecture leadership

Cloud architecture

Microservices design

Event-driven architecture

PostgreSQL & data modeling

Performance optimization

Security & compliance

Team mentorship

Technical leadership

Tools

AWS

PostgreSQL

Redis

GraphQL

ECS/EKS

Job description

Machine Learning Technologies, LLC seeks a senior Cloud Architect to lead the end-to-end architecture for high-traffic, customer-facing web applications. You will design scalable microservices-based and event-driven solutions using Node.js, REST, and GraphQL, and define relational and non-relational data models optimized for high-volume OLTP workloads on PostgreSQL.

You will also create architecture blueprints covering application layers, data flows, integration, observability, and deployment