Solutions Architect 5 (AI Architect)
3Core Systems , Inc Peoria, Illinois, United States
Software Development · 51-200 employees
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About the role
The AI Solutions Architect will collaborate with business stakeholders and technical teams to define and design scalable enterprise AI and Generative AI solutions. The role focuses on discovery, architectural guidance, and ensuring alignment with enterprise standards across hybrid cloud and on-premises environments.
What they look for
Requirements
Candidates must have a bachelor's degree and at least 10 years of experience in solution architecture and enterprise AI implementation. Proficiency in cloud platforms, modern integration patterns, and the ability to facilitate discovery sessions with stakeholders are essential.
Full description
Role: Solutions Architect 5 (AI Architect)
Duration: 12 months
Location: Peoria, IL or Irving, TX (Full-onsite/ 5 days a week)
Job Description: This requisition is for an AI Solution Architect contractor to support existing Caterpillar architects in shaping and defining business-driven enterprise AI and data use cases, including Generative AI. The resource will participate in business discovery, translate use cases into scalable solution designs, and provide architectural guidance to internal development teams across hybrid enterprise environments.
Position’s Contributions to Work Group:
- This
role is intended for 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 use cases, including Generative AI.
- Success
in this role requires strong discovery, solution architecture, and cross-team collaboration skills.
- The
role operates across hybrid on-premises and cloud environments and supports solution definition using approved enterprise platforms, services, and architectural patterns.
- It
is primarily focused on discovery, solution architecture, and implementation guidance rather than hands-on model development or day-to-day application coding.
Typical task breakdown:
- Partner
with existing architects and technical teams to shape solution approaches for new and evolving business use cases.
- Participate
in discovery sessions with business stakeholders to understand objectives, pain points, constraints, and desired outcomes for proposed use cases.
- Translate
business and functional requirements into solution concepts, architecture recommendations, and implementation considerations that align with enterprise standards.
- 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, and support delivery planning.
- 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.
Education & Experience Required:
- Bachelor’s
degree with 10 years of more of experience in this capacity.
- Any
Cloud certification is a nice to have.
Required Technical Skills
(Required)
· Proven experience designing and implementing enterprise AI and Generative AI solutions, including familiarity with enterprise AI platforms, model integration patterns, 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-agent workflows, and orchestration concepts.
· Experience facilitating discovery sessions, gathering business and functional requirements, and translating them into solution architecture recommendations and implementation considerations.
· Experience designing scalable enterprise solutions across on-premises and cloud environments, including familiarity with distributed computing platforms such as Microsoft Azure, AWS, and/or Google Cloud Platform (GCP), and modern application and integration patterns such as APIs, microservices, containerized workloads, cloud-native architectures, and enterprise identity/security integration.
· Experience guiding internal development teams through implementation planning and solution alignment, including the ability to create reference implementations or lightweight prototypes and apply programming languages and common tools used in enterprise AI and cloud solution development.
· Ability to create reference implementations or lightweight prototypes to help internal development teams understand and apply recommended solution patterns for new use cases.
· Working knowledge of programming languages and common tools used in enterprise AI and cloud solution development, such as Python, JavaScript/TypeScript, REST APIs, SDKs, notebooks, and containerized application patterns, sufficient to create reference implementations, review technical approaches, and guide internal development teams.
· Strong communication, facilitation, and collaboration skills, including the ability to work effectively with both business stakeholders and technical teams.
Preferred Qualifications:
· Experience with specific technologies, platforms, frameworks, or specialized approaches such as Azure OpenAI, Amazon Bedrock, Vertex AI, AI Refinery, Microsoft Foundry, LangChain, LangGraph, GraphRAG, Snowflake, Dataiku, Agent Skills/agent harness patterns, MCP servers, and similar enterprise AI and data platforms.
· Experience with container platforms, orchestration technologies, or scalable deployment patterns such as Kubernetes, AKS, EKS, or similar enterprise hosting environments.
· Experience developing reusable architecture patterns, reference implementations, or solution accelerators to support adoption across multiple teams or business use cases.
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