Software Developer (.net, SQL) Turning AI Engineer

Overview

We are seeking a driven and capable Software Developer with a strong background in .NET technologies who is expanding into the field of Artificial Intelligence. This role is ideal for someone who has spent several years developing enterprise applications using technologies like .NET, VB, and SQL Server and is now eager to apply that foundation to modern AI-driven projects. You ll work in a hybrid environment that values both software engineering fundamentals and a growing proficiency in machine learning and data science.

This is an exciting opportunity for a developer who is retooling their skills recently learning Python, machine learning libraries, and AI practices and who wants to blend those with deep knowledge of back-end systems and enterprise software workflows.

Key Responsibilities

• Develop, support, and maintain .NET and SQL-based backend systems while contributing to new AI feature development.
• Collaborate with AI and data science teams to bridge existing enterprise systems with AI models and logic.
• Assist in building, training, and validating machine learning models and integrating them into production systems.
• Use existing SQL Server and application-layer knowledge to prepare, query, and transform data for AI workflows.
• Write clean, maintainable code in both traditional (VB/.NET) and emerging (Python) tech stacks.
• Document system integrations, code changes, and AI deployment processes to ensure maintainability and clarity.
• Stay informed on modern ML/AI tools, trends, and engineering best practices to enhance development quality.
• Participate in technical discussions, sprint planning, and collaborative code reviews.

Qualifications

• Bachelor s degree in Computer Science, Engineering, or a related field.
• 3 6 years of experience as a Software Developer, ideally with strong .NET, VB, and SQL Server expertise.
• Recent hands-on exposure to AI/ML development (bootcamp, self-study, side projects, or formal coursework).
• Solid grasp of Python and libraries like scikit-learn, TensorFlow, or PyTorch.
• Understanding of supervised and unsupervised learning, data preparation, and model evaluation.
• Ability to work across legacy systems and modern frameworks with flexibility and initiative.
• Experience with Git, Agile development environments, and basic DevOps practices.
• Excellent communication, organization, and critical thinking skills.