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Full Stack Software Engineer

Trilyon — United States · Posted ~1 day ago

Hybrid

Skills

Node.js React Kotlin AWS API design Distributed systems Data modeling Cloud infrastructure AWS Lambda DynamoDB RDS S3

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Summary

A full-stack engineering role focused on creating scalable enterprise applications. Responsibilities include frontend and backend development, cloud architecture, data systems, automation, and AI-enabled workflows.

Highlights

Opportunity to build enterprise-scale software with modern cloud technologies, AI integrations, distributed systems, and advanced architecture challenges.

Description

1st Preference: Orange County, CA /Irvine, CA2nd Preference: Bellevue, WA /Seattle, WAWork Schedule: Onsite 3 days per week Full-Stack Development · Node.js backend services and React-based front-end development · Experience with enterprise UI frameworks such as Meridian Backend and API Engineering · Kotlin or similar backend technologies for service development · API design and integration across distributed systems · Experience designing event-driven systems using AWS Lambda, SQS, SNS, and related serverless services Data Modeling and Storage Architecture · Strong experience designing data models and storage strategies for scalable applications and analytics systems · Ability to select and implement appropriate storage solutions based on access patterns, performance requirements, and data lifecycle considerations · Hands-on experience with AWS data services including DynamoDB, RDS, Redshift, OpenSearch and S3 · Experience designing schemas, optimizing queries, and supporting analytics workloads · Integration with BI platforms such as QuickSight AI Integration · Experience integrating AI-powered workflows and natural language interfaces · Prompt engineering and AI-assisted automation Cloud Infrastructure and DevOps · AWS services, infrastructure in code using CDK, and deployment pipelines Workflow Automation and System Integration · Enterprise workflow orchestration and approvals systems · Integration with multiple internal platforms and data sources Quality Assurance · Automated testing frameworks, user acceptance coordination, and performance validation