Senior .NET Engineer with AI

EPAM is a global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, EPAM empowers clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience
• 5+ years of professional experience in software development using C# and .NET technologies (ASP.NET, ASP.NET Core)
• Hands-on experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform
• Strong understanding of cloud-native architectures and tools like Docker, Kubernetes, or serverless frameworks
• Demonstrated hands-on experience integrating and leveraging AI technologies
• Ability to evaluate, select, and implement AI models and frameworks beyond basic tool usage
• Strong understanding of AI/ML concepts including model training, data preprocessing, and prompt engineering
• Proven track record applying AI for process automation, analytics, or product enhancement
• Familiarity with AI adoption limitations and best practices
• Capacity to explain AI concepts to technical and non-technical stakeholders
• Proficiency with relational and non-relational databases including SQL Server, PostgreSQL, MongoDB, or DynamoDB
• Hands-on experience with RESTful API design and development
• Familiarity with CI/CD pipelines and tools such as Azure DevOps, Jenkins, or GitHub Actions
• Solid understanding of software development best practices including Agile, unit testing, and version control (Git)
• Excellent problem-solving and analytical skills
• Effective communication and collaboration skills

• Design, develop, test, and maintain web-based applications, services, and APIs using .NET technologies (C#, ASP.NET Core)
• Collaborate with Product Managers, Designers, and other Engineers to define application requirements and architecture
• Deploy, integrate, and monitor software on cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform
• Implement cloud-native principles using serverless computing, containers (Docker, Kubernetes), and cloud storage solutions
• Integrate and leverage AI technologies in projects
• Evaluate, select, and implement AI models and frameworks beyond basic tool usage
• Identify opportunities to apply AI for process automation, analytics, or product enhancement
• Explain AI concepts and workflows to technical and non-technical stakeholders
• Ensure applications are secure, high-performing, and scalable through best practices in security, optimization, and cloud architecture
• Troubleshoot and resolve technical issues in production and non-production environments
• Participate in code reviews to ensure code quality, reusability, and maintainability
• Automate CI/CD pipelines to streamline deployment and enable continuous delivery
• Stay updated on trends in .NET frameworks, cloud, AI technologies, and development tools
• Mentor junior engineers and contribute to team knowledge base

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