Designs, develop, test, and deploy scalable full-stack applications using .NET and React
Builds and maintain RESTful APIs and backend services using C# and ASP.NET Core
Develops responsive, user-friendly front-end interfaces using React, TypeScript, HTML, and CSS
Implements cloud-native solutions on AWS (compute, storage, networking, monitoring, security)
Automates infrastructure provisioning and environment management using Terraform. Troubleshoots and resolve production issues across application and cloud infrastructure layers
Writes secure, clean, maintainable, and well-documented production code. Contributes to architecture, design reviews, and technical decision-making
Collaborates with cross-functional teams (product, QA, DevOps, security) in agile sprints
Supports CI/CD pipelines and improve release reliability, performance, and resiliency
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on experience in full-stack application development and system design
Strong proficiency in C#, .NET, and ASP.NET Core
Strong front-end experience with React (with TypeScript). Practical experience with AWS services and cloud deployment patterns
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Hands-on Terraform experience for Infrastructure as Code. Experience with relational and/or NoSQL databases and query optimization
Strong debugging, testing, and performance tuning skills
Understanding of SDLC, secure coding, and agile development practices
Familiarity with CI/CD, application resiliency, and observability best practices
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Experience with containerization and orchestration (Docker, Kubernetes, ECS/EKS)
Knowledge of microservices and event-driven architecture
Familiarity with automated testing frameworks and test strategy
Experience with monitoring/logging tools (CloudWatch, ELK, Datadog, etc.). Exposure to enterprise-scale distributed systems
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