Skip to main content
Loading
loadingbar
Loading, Please wait..!!

Artificial Intelligence Engineer

  • Artificial Intelligence Engineer job type Posted on: Nov 12, 2026
  • Artificial Intelligence Engineer experience level Covetus
  • Artificial Intelligence Engineer employment type Mundelein, Illinois
  • Artificial Intelligence Engineer employment type Onsite
  • Artificial Intelligence Engineer salary Full-time

Point Apply Here APPLY LATER

Curious about compensation?

Explore the historical salary trends, average pay, and estimated compensation for Artificial Intelligence Engineer roles in Illinois.

View Salary Guide →

Job Title :

Artificial Intelligence Engineer

Job Type :

Full-Time

Job Location :

Mundelein Illinois United States

Remote :

No

Jobcon Logo Job Description :

Job Description

Job Title: GenAI Architect

\n

Location: New York City, NY (Onsite/Local Candidates Preferred)

\n

Experience: 10+ Years

\n

Visa: Open to All Visa Types

\n


\n

Job Summary:

\n

We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures.

\n

The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams.

\n


\n

Key Responsibilities:

\n
    \n
  • Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks.
  • \n
  • Lead the development and implementation of scalable AI applications and intelligent automation solutions.
  • \n
  • Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation.
  • \n
  • Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures.
  • \n
  • Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems.
  • \n
  • Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions.
  • \n
  • Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability.
  • \n
  • Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI.
  • \n
  • Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures.
  • \n
  • Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle.
  • \n
\n


\n

Required Technical Skills:

\n
    \n
  • 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains.
  • \n
  • Strong hands-on experience designing and implementing Generative AI and LLM-based applications.
  • \n
  • Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems.
  • \n
  • Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling.
  • \n
  • Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
  • \n
  • Proficiency in Python and experience developing enterprise-grade applications and APIs.
  • \n
  • Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs.
  • \n
  • Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
  • \n
  • Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma.
  • \n
  • Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization.
  • \n
  • Experience with enterprise security, data privacy, access controls, and responsible AI practices.
  • \n
\n


\n

Preferred Qualifications:

\n
    \n
  • Experience architecting and delivering enterprise-scale GenAI solutions from concept to production.
  • \n
  • Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines.
  • \n
  • Experience with fine-tuning, model customization, and prompt optimization.
  • \n
  • Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation.
  • \n
  • Excellent communication, stakeholder management, and technical leadership skills.
  • \n
\n


Jobcon Logo Position Details

Posted:

Nov 12, 2026

Reference Number:

7d8cc6d2d21ed0f9

Employment:

Full-time

City:

Mundelein

Job Origin:

ziprecruiter

Share this job:

  • linkedin

Jobcon Logo
A job sourcing event
In Dallas Fort Worth
Aug 19, 2017 9am-6pm
All job seekers welcome!

Artificial Intelligence Engineer    Apply

Click on the below icons to share this job to Linkedin, Twitter!

Job Description

Job Title: GenAI Architect

\n

Location: New York City, NY (Onsite/Local Candidates Preferred)

\n

Experience: 10+ Years

\n

Visa: Open to All Visa Types

\n


\n

Job Summary:

\n

We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures.

\n

The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams.

\n


\n

Key Responsibilities:

\n
    \n
  • Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks.
  • \n
  • Lead the development and implementation of scalable AI applications and intelligent automation solutions.
  • \n
  • Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation.
  • \n
  • Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures.
  • \n
  • Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems.
  • \n
  • Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions.
  • \n
  • Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability.
  • \n
  • Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI.
  • \n
  • Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures.
  • \n
  • Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle.
  • \n
\n


\n

Required Technical Skills:

\n
    \n
  • 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains.
  • \n
  • Strong hands-on experience designing and implementing Generative AI and LLM-based applications.
  • \n
  • Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems.
  • \n
  • Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling.
  • \n
  • Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
  • \n
  • Proficiency in Python and experience developing enterprise-grade applications and APIs.
  • \n
  • Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs.
  • \n
  • Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
  • \n
  • Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma.
  • \n
  • Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization.
  • \n
  • Experience with enterprise security, data privacy, access controls, and responsible AI practices.
  • \n
\n


\n

Preferred Qualifications:

\n
    \n
  • Experience architecting and delivering enterprise-scale GenAI solutions from concept to production.
  • \n
  • Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines.
  • \n
  • Experience with fine-tuning, model customization, and prompt optimization.
  • \n
  • Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation.
  • \n
  • Excellent communication, stakeholder management, and technical leadership skills.
  • \n
\n


Loading
Please wait..!!