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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Software Engineer - **Company:** AgreeYa Solutions, Inc. - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Salary:** $149,760.0 - **Contract:** Permanent contract - **Skills:** Flutter, Web Interfaces, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Cloudfront, Amazon S3, Apple IOS, Automation of Tests, Cloud Computing, Cloud Engineering, Code Generation, Code Review, Continuous Integration, Amazon DynamoDB, Fault Tolerance, Python (Programming Language), Node.Js, Performance Tuning, Rapid Prototyping Process, Software Engineering, Web Applications, AWS Cdk, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Generative AI, Backend, Cloudformation, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Dart, Front End Software Development, Functional Programming, Cloud Optimization, Cloudwatch, Api Gateway, Restful APIs, Amazon Simple Queue Service (SQS), Multiplatform, Serverless Computing, Microservices - **Published:** July 1, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a8ef5b72d2dec1d8 ## About the Role Do you have experience in Web applications?, * 5+ years of professional software engineering experience; bachelor's degree in computer science or engineering, or 7+ years of equivalent experience * Strong full-stack proficiency across mobile/cross-platform (Flutter/Dart), web (React/JavaScript), and backend (Python, Node.js, Java/Spring Boot) * Hands-on AWS experience across a broad range of services including but not limited to Lambda, API Gateway, DynamoDB, Kinesis, OpenSearch, S3, Firehose, Event Bridge, and SSM * Experience with CI/CD, infrastructure-as-code, and serverless deployment patterns * Demonstrated use of AI/GenAI tools in a professional development setting, understanding of prompt engineering, context management, and AI tool limitations * Familiarity with AWS CDK or SAM for infrastructure provisioning is a plus * Exposure to agentic AI workflows and multi-agent systems is a plus * AWS certification (Solutions Architect, Developer, or equivalent) is a plus ## Description * AWS Cloud, Serverless & Microservices Architecture * Design and deliver cloud-native, microservices-based solutions on AWS, applying microservices principles across the full stack - frontend, backend, and cloud infrastructure - to build scalable, secure, and highly available systems, leveraging a broad and growing set of services including but not limited to: * Compute: Lambda, Step Functions * API, Auth & CDN: API Gateway, Cognito, CloudFront * Messaging & Events: SQS, SNS, Event Bridge, Kinesis * Data: DynamoDB, S3, Aurora Serverless, OpenSearch, Kinesis Firehose * Configuration: SSM Parameter Store * Observability: CloudWatch, X-Ray * IaC: CDK, SAM, CloudFormation * And more across the broader AWS ecosystem * Build and maintain scalable REST APIs using API Gateway and Lambda * Support cloud cost optimization, security posture, and performance tuning efforts * Implement CI/CD pipelines, infrastructure-as-code (AWS CDK/SAM), and blue/green deployment strategies * Ensure production readiness through observability, automated testing, and monitoring * Full-Stack, Microservices & Cross-Platform Development * Design, develop, test, and deploy full-stack applications and microservices across Flutter/Dart (mobile & cross-platform), React/JavaScript (web), and Python/Node.js/Java/Spring Boot (backend) * Build responsive, performant web interfaces using React and JavaScript, ensuring seamless user experiences across devices * Develop robust backend services and RESTful APIs using Java/Spring Boot, Python, and Node.js following microservices design principles * Create and maintain cross-platform mobile and web applications using Flutter/Dart, delivering consistent experiences across iOS, Android, and web * Apply microservices best practices including service decomposition, independent deploy ability, and fault tolerance across the full stack * AI-Assisted Engineering & Rapid Prototyping * Rapidly prototype new product concepts using GenAI and LLM platforms * Apply AI-assisted development tools to accelerate code generation, testing, documentation, and code review * Evaluate AI-generated outputs for correctness, security, and production readiness * Follow team-level standards and best practices for AI tool adoption * Contribute to ideate * prototype * validate * ship cycles within fast-moving engineering teams * Collaboration & Mentorship * Participate in code reviews and contribute to engineering best practices * Support and mentor mid-level and junior engineers on design, cloud practices, and AI tool usage * Promote a culture of quality, continuous improvement, and learning ## Related Videos - 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