Solutions Architect 5 AI Architect

Chateck Inc.
Peoria, IL, United States
3 days ago
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Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Compensation
$166,400 - $170,560
Working hours
Regular working hours
Job source

Tech stack

LangGraph Framework JavaScript (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Software Design Patterns Identity and Access Management Python (Programming Language) Machine Learning Natural Language Processing
+31 more
OpenAI Cloud Services Search Technologies Software Deployment TypeScript Enterprise Search Google Cloud Cloud Platform System Snowflake Multi-Agent Systems Prompt Engineering Google Vertex AI IT Architecture Generative AI HybridCloud Agentic-AI AWS ECS Containerization AI Platforms Kubernetes Amazon Bedrock Data Analytics Azure AKS Data Management Dataiku Graph RAG Restful APIs Model Context Protocol Prompt Orchestration Network Server Microservices

Job description

Our client is seeking a highly experienced AI Solutions Architect for an enterprise AI architecture opportunity with one of our clients, a leading global organization in the manufacturing industry.

The ideal candidate will bridge business requirements and technical execution by defining scalable, secure, and production-ready AI and Generative AI solutions.

This is a senior-level architecture position focused on technical discovery, enterprise solution design, technology evaluation, architectural strategy, and implementation guidance across hybrid cloud and on-premises environments.

The role emphasizes enterprise AI architecture and technical leadership rather than hands-on machine learning model development or day-to-day application coding., * Partner with enterprise architects, business stakeholders, and technical teams to identify AI, Generative AI, and data-driven business opportunities.

  • Lead business and technical discovery sessions to understand objectives, functional requirements, constraints, and expected outcomes.
  • Translate business requirements into scalable enterprise solution architectures and actionable technical implementation strategies.
  • Architect enterprise AI solutions incorporating Retrieval-Augmented Generation (RAG), vector databases, enterprise search, prompt orchestration, Agentic AI, and multi-agent workflows.
  • Evaluate AI platforms, architectural alternatives, integration patterns, technical dependencies, implementation risks, and technology feasibility.
  • Provide architectural direction and technical guidance to engineering teams throughout solution planning and implementation.
  • Collaborate with AI engineers, data scientists, ML engineers, application developers, and business domain experts.
  • Develop lightweight prototypes and reference implementations to validate architectural recommendations and demonstrate solution patterns.
  • Recommend enterprise AI platforms, cloud services, APIs, SDKs, and reusable integration architectures.
  • Ensure architecture designs align with enterprise security, identity management, governance, compliance, and technology standards.
  • Develop architecture diagrams, technical documentation, design specifications, and implementation guidelines.
  • Establish reusable enterprise AI reference architectures, design patterns, and solution accelerators to support organization-wide AI adoption.

Requirements

  • Bachelor’s degree with 10+ years of relevant professional experience in enterprise solution architecture, AI architecture, or related technical architecture roles.
  • Demonstrated experience designing and implementing enterprise AI and Generative AI solutions.
  • Strong understanding of enterprise AI architecture concepts, including:
  • Natural Language Processing (NLP)
  • Retrieval-Augmented Generation (RAG)
  • Vector databases and vector search
  • Enterprise search architectures
  • Prompt engineering and orchestration
  • Agentic AI and multi-agent workflows
  • AI model integration and production deployment patterns
  • Proven ability to conduct business and technical discovery sessions and translate requirements into enterprise architecture solutions.
  • Experience designing scalable architectures across hybrid on-premises and cloud environments.
  • Working knowledge of at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (Google Cloud Platform).
  • Strong understanding of modern application and integration architectures, including APIs, microservices, containers, cloud-native solutions, and enterprise security integration.
  • Ability to develop lightweight prototypes and reference implementations to demonstrate architectural approaches.
  • Working knowledge of Python, JavaScript/TypeScript, REST APIs, SDKs, and development notebooks.
  • Experience providing architectural direction and implementation guidance to engineering and development teams.
  • Excellent communication, stakeholder management, technical facilitation, and cross-functional collaboration skills.

Preferred Qualifications

Experience with one or more of the following technologies and platforms is highly desirable.

Enterprise AI Platforms

  • Azure OpenAI
  • Amazon Bedrock
  • Google Vertex AI
  • AI Refinery
  • Microsoft Foundry

AI Frameworks and Architecture

  • LangChain
  • LangGraph
  • GraphRAG
  • Agent Skills
  • Agent Harness Patterns
  • Model Context Protocol (MCP) Servers
  • Multi-agent orchestration

Data Platforms

  • Snowflake
  • Dataiku

Cloud and Container Technologies

  • Kubernetes
  • Azure Kubernetes Service (AKS)
  • Amazon Elastic Kubernetes Service (EKS)

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