Sr .Net Developer(Azure Focused)

GBIT (Global Bridge InfoTech Inc); McKinney (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

GBIT (Global Bridge InfoTech Inc) seeks a Senior .NET Developer with Azure and hands-on AI/GenAI experience to join a platform engineering team. You will build modular, reusable enterprise capabilities and APIs that scale across products and business units.

This AI-forward role requires using AI coding agents to accelerate development, while applying engineering judgment to validate, test, and improve AI-generated output. Onsite McKinney, TX, 5 days a week, long-term contract.

Qualifications

• Strong hands-on experience with C# / .NET Core / ASP.NET Core.
• Strong EF Core experience.
• Strong experience with GraphQL.
• Experience building enterprise platforms, products, APIs, or reusable business capabilities.
• Hands‑on experience with AI/GenAI in software development.
• Experience using AI coding agents or AI-assisted development tools to increase developer productivity.
• Experience creating or following AI rules, guardrails, policies, and context-management practices to prevent incorrect or inconsistent AI output.
• Ability to direct, review, test, challenge, and validate AI-generated code rather than simply accepting AI output.
• Strong understanding of software architecture, design patterns, coding standards, security, and development best practices.
• Demonstrated experience decomposing product features into smaller, reusable capabilities. Mandatory.
• Strong automated testing experience using xUnit, Playwright, or similar frameworks.
• Ability to distinguish between verified facts/results and assumptions or proposed solutions.
• Strong problem-solving and analytical skills with an evidence-driven approach.

Responsibilities

• Design and develop scalable backend services using C#, .NET Core, and EF Core.
• Build reusable enterprise capabilities that can be configured and integrated across multiple applications.
• Develop APIs and services using GraphQL and modern application architecture patterns.
• Work extensively with Azure, including App Service, Azure SQL, Key Vault, and Azure Functions.
• Use AI coding agents and GenAI tools as part of the daily development workflow to accelerate coding, analysis, testing, debugging, documentation, and refactoring.
• Create and maintain rules, guardrails, policies, and context for AI coding agents to ensure consistent and reliable output.
• Direct AI agents effectively by providing appropriate context, requirements, constraints, and technical guidance.
• Critically review and validate AI-generated code for correctness, security, performance, maintainability, architecture, and coding standards before deployment.
• Decompose large product features into smaller, reusable business capabilities that can be independently developed, configured, and consumed.
• Build automated tests using xUnit, Playwright, or similar frameworks; use AI-assisted testing where appropriate.
• Contribute to Server-Driven UI (SDUI) and other server-driven application patterns when applicable.
• Work with enterprise ontology/entity-relationship models where required.
• Develop solutions that support scalability, security, governance, observability, configurability, and maintainability.
• Continuously evaluate how AI can be used to improve engineering productivity without compromising software quality.
• Verify assumptions through testing, documentation, code analysis, and other evidence before shipping.
• Collaborate with architects, product teams, and other engineers to evolve the platform as requirements and learning change.

Skills

C# / .NET Core

GraphQL

Azure

AI/GenAI in software development

Code review AI output

Testing automation

Tools

EF Core

xUnit

Playwright

SDUI

Job description

Duration: Long-Term Contract

Work location: McKinney TX (5 days onsite)

Onsite interview attendance is mandatory:

• First round: Irving, TX
• Second round: McKinney, TX

Job Overview

We are looking for a Senior .NET Developer with strong Azure and hands-on AI/GenAI experience to join a platform engineering team building reusable, enterprise-grade business capabilities.

This is an AI-forward engineering role. We are looking for someone who actively uses AI coding agents and GenAI tools to accelerate software development, while applying strong engineering judgment to direct, validate, test, and improve AI-generated output.

The team is building a reusable platform rather than developing one-off solutions for individual applications or clients. Engineers will create modular capabilities that can be configured and reused across multiple products, business units, and use cases.

Key Responsibilities

• Design and develop scalable backend services using C#, .NET Core, and EF Core.
• Build reusable enterprise capabilities that can be configured and integrated across multiple applications.
• Develop APIs and services using GraphQL and modern application architecture patterns.
• Work extensively with Azure, including App Service, Azure SQL, Key Vault, and Azure Functions.
• Use AI coding agents and GenAI tools as part of the daily development workflow to accelerate coding, analysis, testing, debugging, documentation, and refactoring.
• Create and maintain rules, guardrails, policies, and context for AI coding agents to ensure consistent and reliable output.
• Direct AI agents effectively by providing appropriate context, requirements, constraints, and technical guidance.
• Critically review and validate AI-generated code for correctness, security, performance, maintainability, architecture, and coding standards before deployment.
• Decompose large product features into smaller, reusable business capabilities that can be independently developed, configured, and consumed.
• Build automated tests using xUnit, Playwright, or similar frameworks and use AI-assisted testing where appropriate.
• Contribute to Server-Driven UI (SDUI) and other server-driven application patterns when applicable.
• Work with enterprise ontology/entity-relationship models where required.
• Develop solutions that support scalability, security, governance, observability, configurability, and maintainability.
• Continuously evaluate how AI can be used to improve engineering productivity without compromising software quality.
• Verify assumptions through testing, documentation, code analysis, and other evidence before shipping.
• Collaborate with architects, product teams, and other engineers to evolve the platform as requirements and learning change.

Required Skills & Experience

• Strong hands-on experience with C# / .NET Core / ASP.NET Core.
• Strong EF Core experience.
• Strong experience with GraphQL.
• Experience building enterprise platforms, products, APIs, or reusable business capabilities.
• Hands‑on experience with AI/GenAI in software development.
• Experience using AI coding agents or AI-assisted development tools to increase developer productivity.
• Experience creating or following AI rules, guardrails, policies, and context-management practices to prevent incorrect or inconsistent AI output.
• Ability to direct, review, test, challenge, and validate AI-generated code rather than simply accepting AI output.
• Strong understanding of software architecture, design patterns, coding standards, security, and development best practices.
• Demonstrated experience decomposing product features into smaller, reusable capabilities. Mandatory.
• Strong automated testing experience using xUnit, Playwright, or similar frameworks.
• Ability to distinguish between verified facts/results and assumptions or proposed solutions.
• Strong problem-solving and analytical skills with an evidence-driven approach.

Nice to Have

• Experience with Server-Driven UI (SDUI) or similar server-driven application architectures.
• Experience with ontology, entity-relationship modeling, or enterprise domain modeling.
• Experience working on a dedicated platform engineering team.
• Experience building configurable, plug-and-play enterprise components.

What We're Looking For

We are looking for an engineer who sees AI as a development multiplier, not simply a technology to talk about.

The ideal candidate knows how to:

Understand the requirement → break it into reusable capabilities → use AI to accelerate implementation → provide the right context and guardrails → review AI-generated output → test and validate it → improve it → ship reliable enterprise-grade software.

You should be comfortable using AI throughout the development lifecycle while maintaining ownership of the final technical outcome.

The goal is to build capabilities once and reuse them many times — allowing teams to select a capability, configure it, integrate it, and deploy it instead of rebuilding similar functionality from scratch for every application or client.

This is a platform-focused, AI-forward engineering environment where the team continuously evaluates new approaches and uses AI extensively to improve development speed and productivity.