.NET Engineer

Job Summary

The AI Training Specialist will leverage their software engineering background to evaluate, benchmark, and optimize AI models training on backend programming languages and cloud logic. Key functions include writing baseline C# code samples, checking cloud deployment architecture diagrams for validity, diagnosing model gaps across AWS and Azure environments, and providing clear, structured technical feedback to optimize the model's operational accuracy.

Qualification

Candidates must meet the following baseline communication, structural, and environmental standards:

• Communication Mastery: Exceptional written and verbal English communication skills, specifically demonstrating a talent for explaining complex programming concepts, logic choices, and cloud configurations in clear, scannable prose.
• Technical Workspace Setup: Self-motivated and fully equipped to maintain absolute productivity, data safety, and strict deadline adherence in an independent, remote working environment.
• Industry Currency: Up-to-date, comprehensive knowledge of modern industry standards, design patterns (e.g., microservices, clean architecture), tools, and frameworks within the broader .NET ecosystem.

Experience

Candidates must demonstrate a robust background in production-level backend development, cloud execution, and technical documentation synthesis:

Core Engineering Mastery

• Production .NET & C# Experience: Extensive, verified hands-on experience designing, writing, and maintaining backend solutions using .NET and C# in active production environments.
• Dual-Cloud Ecosystem Fluency: Demonstrated technical expertise deploying, configuring, and managing enterprise cloud platforms across both Amazon Web Services (AWS) and Microsoft Azure.
• System Architecture & Documentation: Direct experience writing and optimizing clean, maintainable code snippets, modeling architectural diagrams, and authoring comprehensive technical documentation.

Problem-Solving & Architecture

• Advanced Analytical Troubleshooting: Strong problem-solving skills, with a proven track record of breaking down complex, multi-layered technical bugs, cloud configuration conflicts, or systemic database logic blocks.
• Modern Backend Strategy: Practical experience sharing and implementing best practices related to scalable backend development, cloud service integration, and modern application design.
• Distributed Cloud Systems (Preferred): Prior experience working with geographically distributed teams on large-scale, high-concurrency cloud applications.
• DevOps & Infrastructure (Preferred): Familiarity with modern DevOps practices, containerization, and continuous integration/continuous deployment (CI/CD) pipelines within .NET-centric environments.
• Data or AI Exposure (Preferred): Prior experience contributing to machine learning data annotation, open-source documentation, or data-driven software engineering projects.

Key Responsibilities

Model Evaluation & Output Optimization

• Audit Technical Outputs: Evaluate, analyze, and systematically enhance AI model outputs related to .NET, C#, AWS, and Azure ecosystems to ensure maximum accuracy and safety.
• Identify Behavioral Gaps: Spot potential blind spots, structural edge cases, or gaps in the model's comprehension of advanced programming concepts and suggest algorithmic corrections based on your real-world engineering history.
• Validate Code Quality: Write, review, and optimize robust code snippets, backend scripts, and multi-cloud architectural diagrams to serve as gold-standard training data.

Domain-Specific Guidance & Best Practices

• Provide Expert Feedback: Leverage your deep knowledge of C# compilation, runtime behaviors, and enterprise patterns to provide domain-specific feedback to diverse technical challenges.
• Enforce Scalability Standards: Inject real-world best practices regarding scalable backend development, asynchronous programming, microservice messaging, and seamless cloud security integrations into the training pipeline.

Global Collaboration & Communication

• Partner with Global Teams: Collaborate asynchronously and synchronously within a remote, global network of tech experts, contributing unique engineering insights to drive continuous model iteration.
• Translate Complex Concepts: Communicate complex technical concepts with absolute clarity, providing well-structured, scannable feedback suitable for both deep-tech engineers and non-technical model orchestrators.

Skills Required:

• Computer / Software / It / Data