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Kernel Solutions Jobs in Illinois (NOW HIRING)

Neshent Technologies

Applied AI Architect

Golf, IL

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI ... Define and implement AI/ML architecture and solutions. * Work closely with engineering and business ...

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Kernel Solutions information

What is the difference between Kernel Solutions vs Network Support Specialist?

AspectKernel SolutionsNetwork Support Specialist
Required CredentialsIT certifications, knowledge of kernel and system architectureNetworking certifications, knowledge of network protocols and hardware
Work EnvironmentData centers, software development teams, IT departmentsNetwork operations centers, client sites, IT support teams
Employer & Industry UsageTech companies, software firms, IT service providersTelecom, internet service providers, corporate IT departments

Kernel Solutions professionals focus on system-level software, kernel development, and troubleshooting, often working closely with hardware and OS architecture. Network Support Specialists primarily handle network infrastructure, troubleshooting connectivity issues, and maintaining network security. While both roles require IT knowledge, Kernel Solutions roles are more software and system-centric, whereas Network Support Specialists focus on network hardware and protocols.

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Kernel Solutions jobs near you
Infographic showing various Kernel Solutions job openings in Illinois as of August 2026, with employment types broken down into 69% Full Time, 27% Part Time, and 4% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Applied AI Architect

Neshent Technologies

Willowbrook, IL

Full-time

Posted 19 days ago

Job description

We are looking for an Applied AI Architect with strong hands-on experience in AI/ML architecture, development, and production deployment. The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems.

Must-Have Technical Skills
  • Strong hands-on experience in AI/ML development and production deployment.
  • Experience with Databricks, MLflow, Unity Catalog, Delta Lake, and model serving.
  • Experience with Azure AI Foundry and modern AI/ML platforms.
  • Strong knowledge of RAG and LLM application architecture.
  • Experience building multi-agent systems and workflows.
  • Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK.
  • Strong Python development skills for production AI/ML applications.
  • Experience with CI/CD, MLOps, and AIOps.
  • Knowledge of LLM/RAG/agent evaluation, observability, tracing, and monitoring.
  • Experience with production debugging and performance optimization.
  • Ability to create reusable AI accelerators, templates, skills, and reference implementations.
Roles & Responsibilities
  • Define and implement AI/ML architecture and solutions.
  • Work closely with engineering and business teams to build and deploy AI models.
  • Design and develop LLM, RAG, and multi-agent solutions.
  • Establish best practices for AI evaluation, deployment, monitoring, and production support.
  • Improve and standardize applied AI delivery patterns.
  • Accelerate AI adoption through reusable components, templates, and reference architectures.
  • Provide technical leadership and guidance to AI/ML engineering teams.

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