Applied AI Consultant

Ashling•Chicago, IL

2d•$70,000 - $85,000

About The Position

As a consultant, you will independently lead initiatives, providing technical direction during design sessions with clients and Ashling project leads. Your responsibilities will include designing and building cloud solutions leveraging the latest AI and ML capabilities available from major cloud offering providers for clients. You will collaborate with engineers to efficiently implement algorithms within existing production processes and assist in establishing design and coding standards, policies, and procedures across development efforts. Additionally, you will provide recommendations on improving team efficiency from a code reusability standpoint.

Requirements

Bachelor’s degree in computer science or engineering discipline
2+ years of programming experience
2+ years of .NET development experience (C#)
Experience in one of the major cloud providers such as Azure, GCP or AWS
Proven experience implementing LLM capabilities into cloud solutions
Experience with Azure DevOps Pipelines
Interested in intelligent automation market and cloud infrastructure technologies

Nice To Haves

Experience in statistics or numerical methods is a plus but not required
Experience in Power Platform is a plus but not required
Experience with prompt engineering and LLM evaluation frameworks (e.g., Azure AI Foundry evaluation, Ragas) is a plus but not required
Experience building RAG pipelines using Azure AI Search or vector databases is a plus but not required
Familiarity with agent interoperability protocols (MCP, Agent2Agent/A2A) is a plus but not required
Experience with Azure AI Document Intelligence or other OCR/intelligent document processing tools is a plus but not required

Responsibilities

Participate in design sessions with clients and Ashling project leads to provide technical direction on design considerations for development, performance, scalability, availability, maintainability, and reusability.
Leverage numerical methods and testing algorithms for evaluating LLM performance for different use cases.
Collaborate with engineers to implement algorithms efficiently with existing production processes
Assist with design and coding standards, testing pipelines, policies and procedures across development efforts.