Senior Cloud AI Solutions Consultant

Co-Sourcing Partners

$120K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science, Engineering, or practical equivalent
  • 4+ years of professional software development experience
  • 4+ years of hands-on C#/.NET development in production environments
  • Experience designing and deploying solutions on Azure
  • Proven experience integrating LLM or AI capabilities into cloud applications
  • Experience with Azure DevOps pipelines and CI/CD practices
  • Ability to work independently and make technical decisions

Responsibilities

  • Lead client and internal design sessions, providing clear technical direction
  • Design and build cloud-native solutions in Azure with C#/.NET
  • Integrate LLM and AI capabilities into existing production applications
  • Collaborate with engineers to implement designs efficiently
  • Establish and enforce coding standards and architectural patterns
  • Improve team efficiency through reusable components and automation
  • Provide clear technical recommendations to clients and project leadership

Benefits

  • Flexible remote work options
  • Opportunity to work on production-ready cloud solutions
  • Engage with clients in a client-facing role
  • Work in a collaborative team environment
  • Chance to enhance team efficiency and coding standards
Full Job Description
Job Title : Senior Cloud AI Solutions Consultant (.NET / Azure)
Duration : 12 Months
Location : Chicago - Remote

Role Summary
We are seeking a senior, client-facing Cloud AI Solutions Consultant who can lead technical design, make architecture decisions, and deliver production-ready cloud solutions that incorporate LLM and AI capabilities. This role requires strong C#/.NET engineering skills, hands-on Azure cloud experience, and the ability to independently guide clients and delivery teams from design through implementation.
This is not a research or prototype role. You will work on real production systems, integrating AI capabilities into existing applications while ensuring scalability, reliability, and maintainability.
If you are a senior .NET engineer with Azure experience who has implemented AI/LLM capabilities in real production systems and can confidently lead client design conversations, this role is for you.

What You Will Do
  • Lead client and internal design sessions, providing clear technical direction on architecture, performance, scalability, availability, and reuse
  • Design and build cloud-native solutions in Azure using C#/.NET
  • Integrate LLM and AI capabilities into existing production applications, including evaluation of accuracy, cost, latency, and suitability by use case
  • Collaborate with engineers to implement designs efficiently within established production environments
  • Establish and enforce coding standards, architectural patterns, and CI/CD practices
  • Improve team efficiency through reusable components, shared patterns, and pragmatic automation
  • Provide clear, confident technical recommendations to clients and project leadership
Required Experience
  • Bachelor's degree in computer science, Engineering, or equivalent practical experience
  • 4+ years of professional software development experience
  • 4+ years of hands-on C#/.NET development in production environments
  • Experience designing and deploying solutions on Azure (other major cloud platforms acceptable)
  • Proven experience integrating LLM or AI capabilities into cloud-based applications
  • Experience with Azure DevOps pipelines and modern CI/CD practices
  • Ability to work independently, own technical decisions, and operate with minimal oversight
Nice to Have
  • Experience evaluating LLM performance using testing or numerical methods
  • Familiarity with intelligent automation platforms or patterns
  • Experience with Microsoft Power Platform
What This Role Is Not
  • Not a data science or research role
  • Not a junior or mentorship-only position
  • Not focused on model training or academic ML work
Core Competencies
  • Strong architectural judgment and problem-solving skills
  • Clear and confident communication with technical and non-technical stakeholders
  • Proven leadership in improving engineering efficiency and code quality
  • Practical, outcome-focused approach to AI and cloud solutions

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