Senior AI Solutions Architect

3Core Systems, Inc; Peoria (IL); On-site; USD 150,000 - 200,000; Full time

Job summary

3Core Systems, Inc. in Peoria, IL is seeking a Senior AI Solutions Architect for a 12-month contract. You will work with client architects to shape enterprise AI and data use cases, including Generative AI, across hybrid on-prem and cloud environments.

Responsibilities include discovery sessions, translating requirements into scalable designs, and providing architectural guidance to development teams, with a focus on reusable patterns and implementation guidance.

Qualifications

• Bachelor’s degree in Engineering or IT.
• 5+ years in AI/GenAI solution architecture.
• 8+ years enterprise solution architecture across hybrid cloud.

Responsibilities

• Partner with existing architects and technical teams to shape solution approaches for new and evolving business use cases.
• Translate business and functional requirements into solution concepts, architecture recommendations, and implementation considerations.
• Collaborate with cross-functional teams, including architects, internal development teams, engineers, data scientists, machine learning engineers, and domain experts, to refine solution direction, provide implementation guidance.
• Create or demonstrate reference implementations or lightweight prototypes, when appropriate, to illustrate recommended approaches for new or evolving use cases.
• Assess solution options, tradeoffs, dependencies, and technical feasibility for proposed business use cases across hybrid enterprise environments.
• Facilitate alignment between business stakeholders and technical teams by clarifying use case scope, assumptions, constraints, and recommended next steps.
• Support evaluation and recommendation of approved tools, platforms, and solution patterns needed to enable business use cases in alignment with enterprise architecture and governance standards.
• Create clear documentation for proposed solutions, including architecture views, assumptions, dependencies, design considerations, and recommended implementation approaches.
• Contribute to reusable architecture guidance, design patterns, and solution documentation that can support repeatable delivery across similar AI and data use cases.

Skills

AI

AWS

Cloud

GCP

GenAI

Microservices

Python

RAG

REST

Education

Bachelor’s Degree

Tools

Kubernetes

AKS

EKS

LangChain

LangGraph

GraphRAG

Snowflake

Dataiku

Vertex AI

Azure OpenAI

Amazon Bedrock

Job description

Peoria, United States | Posted on 11/11/2026

Job Title: Senior AI Solutions Architect

Location: Peoria, IL, 61602, USA

Duration: 12 months contract.

Must Have Skills/Attributes:

• AI, AWS, Cloud, GCP,Generative AI/GenAI, Microservices, Python, RAG (Retrieval-AugmentedGeneration), REST.

Experience Desired:

• Enterprise AI &Generative AI Solution Architecture (LLMs, RAG, Vector Search, Agentic AI,NLP) (5+ yrs).
• Enterprise SolutionArchitecture across Hybrid Cloud (Azure, AWS, or GCP) (8+ yrs).
• Business Discovery,Requirements Gathering & Solution Design (8+ yrs).
• AI ImplementationLeadership using Python, REST APIs, SDKs, and Reference Implementations(5+ yrs).
• Required MinimumEducation: Bachelor’s Degree.

JOB DESCRIPTION:

Required Education/Experience:

• Bachelor’s degree inEngineering or IT.

Required Qualifications:

• This requisition is foran AI Solution Architect contractor to support existing CLIENTarchitects in shaping and defining business-driven enterprise AI and datause cases, including Generative AI
• The resource willparticipate in business discovery, translate use cases into scalablesolution designs, and provide architectural guidance to internaldevelopment teams across hybrid enterprise environments.

Preferred Qualifications:

• Experience with specifictechnologies, platforms, frameworks, or specialized approaches such asAzure OpenAI, Amazon Bedrock, Vertex AI, AI Refinery, Microsoft Foundry, LangChain, LangGraph, GraphRAG, Snowflake, Dataiku, Agent Skills/agentharness patterns, MCP servers, and similar enterprise AI and dataplatforms.
• Experience withcontainer platforms, orchestration technologies, or scalable deploymentpatterns such as Kubernetes, AKS, EKS, or similar enterprise hostingenvironments.
• Experience developingreusable architecture patterns, reference implementations, or solutionaccelerators to support adoption across multiple teams or business usecases.

Required Technical Skills:

• Proven experiencedesigning and implementing enterprise AI and Generative AI solutions,including familiarity with enterprise AI platforms, model integrationpatterns, solution architecture considerations for production use cases,and modern AI solution approaches such as NLP, RAG, vector-based search,enterprise search, prompt orchestration, agentic AI patterns, multi-agentworkflows, and orchestration concepts.
• Experience facilitatingdiscovery sessions, gathering business and functional requirements, andtranslating them into solution architecture recommendations andimplementation considerations.
• Experience designingscalable enterprise solutions across on-premises and cloud environments,including familiarity with distributed computing platforms such asMicrosoft Azure, AWS, and/or Google Cloud Platform (GCP), and modernapplication and integration patterns such as APIs, microservices,containerized workloads, cloud-native architectures, and enterpriseidentity/security integration.
• Experience guidinginternal development teams through implementation planning and solutionalignment, including the ability to create reference implementations orlightweight prototypes and apply programming languages and common toolsused in enterprise AI and cloud solution development.
• Ability to createreference implementations or lightweight prototypes to help internaldevelopment teams understand and apply recommended solution patterns fornew use cases.
• Strong communication,facilitation, and collaboration skills, including the ability to workeffectively with both business stakeholders and technical teams.

Position’s Contributions to Work Group:

• This role is intendedfor someone who can quickly engage with architects, business stakeholders,and internal development teams to assess needs, evaluate solution options,and define practical solution approaches for enterprise AI and data usecases, including Generative AI.
• Success in this rolerequires strong discovery, solution architecture, and cross-teamcollaboration skills.
• The role operates acrosshybrid on-premises and cloud environments and supports solution definitionusing approved enterprise platforms, services, and architectural patterns.
• It is primarily focusedon discovery, solution architecture, and implementation guidance ratherthan hands-on model development or day-to-day application coding.

Typical task breakdown:

• Partner with existingarchitects and technical teams to shape solution approaches for new andevolving business use cases.
• Participate in discoverysessions with business stakeholders to understand objectives, pain points,constraints, and desired outcomes for proposed use cases.
• Translate business andfunctional requirements into solution concepts, architecturerecommendations, and implementation considerations that align withenterprise standards.
• Collaborate withcross-functional teams, including architects, internal development teams,engineers, data scientists, machine learning engineers, and domainexperts, to refine solution direction, provide implementation guidance,and support delivery planning.
• Create or demonstratereference implementations or lightweight prototypes, when appropriate, toillustrate recommended approaches for new or evolving use cases.
• Assess solution options,tradeoffs, dependencies, and technical feasibility for proposed businessuse cases across hybrid enterprise environments.
• Facilitate alignmentbetween business stakeholders and technical teams by clarifying use casescope, assumptions, constraints, and recommended next steps.
• Support evaluation andrecommendation of approved tools, platforms, and solution patterns neededto enable business use cases in alignment with enterprise architecture andgovernance standards.
• Create cleardocumentation for proposed solutions, including architecture views,assumptions, dependencies, design considerations, and recommendedimplementation approaches.
• Contribute to reusablearchitecture guidance, design patterns, and solution documentation thatcan support repeatable delivery across similar AI and data use cases.