Intermediate Software Engineer - Accounting Automation & AI (HYBRID)

Design and deliver RESTful APIs with ASP.NET Core, and document them clearly using Swagger/OpenAPI for smooth consumer integration. Design data solutions across structured, semi-structured, and unstructured data—covering schema modeling, querying, and performance tuning.

Required Qualifications

• Bachelor’s degree in Computer Science or a related analytical field or equivalent experience
• 3+ years of experience with Microsoft .NET, .NET Core and C#
• 2+ years of experience designing and developing REST APIs
• Experience working in a cloud environment such as Azure or similar tools
• Experience working with source control and CI/CD tools
• Ability to write clean, maintainable, scalable, and well-documented code
• Experience working in Agile/Scrum development environments

Preferred Qualifications

• Experience building and maintaining Infrastructure as Code (IaC) with Terraform to deliver repeatable, reliable environments
• Experience working with relational databases such as SQL Server, Oracle, or similar database technologies.
• Experience working with source control and CI/CD tools such as Azure DevOps, GitHub Actions, Git, or similar technologies.
• Experience developing cloud infrastructure on Microsoft Azure using Terraform modules and best practices to create scalable, secure foundations
• Write clean, maintainable Python to automate workflows and support backend services
• Design and deliver RESTful APIs with ASP.NET Core, and document them clearly using Swagger/OpenAPI for smooth consumer integration
• Experience using Git confidently to collaborate effectively and ship high-quality changes
• Bring curiosity about AI: hands-on familiarity with LLM APIs, prompting, and core AI/ML concepts (at a conceptual level)
• Familiarity with retrieval‑augmented generation (RAG) and context‑engineering techniques to improve response quality and relevance
• Design data solutions across structured, semi-structured, and unstructured data—covering schema modeling, querying, and performance tuning
• Ability to keep AI top of mind: awareness of governance practices such as safe automation, bias considerations, and responsible‑use patterns

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