5+ years of professional software engineering experience developing scalable .NET, cloud-based, or web services applications that support high-volume transactions in highly available environments.
Hands-on experience designing and implementing scalable, resilient, and event-driven applications using .NET and Kafka, with knowledge of distributed systems, stream processing, performance optimization, and cloud-native architectures.
Working experience with IBM MQ, Kafka, Splunk, JSON/XML, caching, performance analysis and profiling, Twelve-Factor App methodology, resiliency patterns, and observability patterns.
Job Responsibilities
Required Qualifications:
Experience owning technical components or features and collaborating effectively within a software delivery team.
4+ years of experience building and deploying cloud-native applications using GCP, Docker, Kubernetes, microservices, and CI/CD practices. Experience with cloud platforms and deployment environments such as PCF, AWS, or GCP.
2+ years of experience working with databases such as MongoDB, Aerospike, PostgreSQL, or comparable relational and NoSQL platforms.
Experience contributing to IT transformation or system modernization initiatives involving legacy platforms, distributed .NET applications, or modern data platforms.
1+ years of hands-on experience with AI/ML implementation, production deployment, or AI-assisted engineering practices.
Hands-on experience or practical exposure to Large Language Models such as GPT, Claude, Gemini, PaLM, or comparable enterprise AI platforms.
Demonstrated hands-on experience using GenAI coding assistants across SDLC workflows, including implementation, refactoring, unit testing, regression support, code reviews, scripting, automation, troubleshooting, and documentation.
Practical familiarity with tools such as GitHub Copilot and/or Claude Code in IDE or CLI-based workflows, with the ability to apply AI assistance to reduce context switching and accelerate delivery beyond code generation.
Working knowledge of agentic workflows, spec-driven development, custom instructions, and prompt engineering, with the ability to apply effective AI-assisted development practices.
Knowledge of Agile methodology and experience in an Agile working environment. Experience with the Atlassian tool stack, including Jira and Confluence.