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.Net Technical Lead/Architect

Qode

South Carolina, South Carolina, United States Hybrid permanent

Posted: April 9, 2026

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Quick Summary

Experience as a .Net Architect is required to lead migration of .NET applications to AWS, with a strong focus on cloud-native development using AWS services such as Lambda and AP.

Job Description

Role: .Net Technical Lead/Architect
Job Overview
Looking for an experienced .NET Architect to lead application migration, modernization, and cloud-native development on AWS. Must have strong hands-on expertise in C#, .NET Core, microservices, and AWS services, with the ability to guide teams and define end-to-end architecture.

Key Responsibilities
• Architect and lead migration of .NET applications to AWS Landing Zones (lift & shift + modernization).
• Break monolithic .NET apps into scalable microservices using .NET Core/.NET 6+.
• Design cloud-native solutions using AWS services: Lambda, API Gateway, SQS, SNS, Step Functions, S3, DynamoDB, Glue, RDS PostgreSQL.
• Provide architectural guidance, solution design, and technical leadership.
• Enable DevOps automation using CI/CD, Docker, Kubernetes/EKS, IaC.
• Ensure scalability, security, resiliency, and cost optimization across AWS workloads.
• Drive engineering best practices, code reviews, and quality frameworks.

Required Skills
• 12+ years in C#, .NET Framework, .NET Core/.NET 6/7/8.
• Strong in microservices, REST APIs, event-driven systems.
• Experience modernizing legacy .NET apps to .NET Core.
• Hands-on with AWS (Lambda, SQS, SNS, Step Functions, S3, RDS, DynamoDB).
• Strong database skills: SQL Server, PostgreSQL, DynamoDB, Redis.
• DevOps experience with CI/CD pipelines, Docker, Kubernetes/EKS.
• Testing tools: xUnit, NUnit, Moq, Testcontainers.
• Strong understanding of architectural patterns (DDD, Clean Architecture).

Preferred
• AWS certification (Solutions Architect / Developer / DevOps).
• Experience in large-scale enterprise modernization programs.
• Strong communication and stakeholder leadership.

Nice-to-Have Skills
• Exposure to Generative AI concepts (LLMs, embeddings, simple RAG patterns).
• Basic understanding of prompt engineering and LLM integration.
• Familiarity with Agentic AI concepts (AI agents, workflow automation).
• Some experience with vector databases (OpenSearch, Pinecone, Redis Vector).
• Awareness of AWS Bedrock services and foundational models (Claude, Llama, Titan).

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