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Job Title: Solution Architect – Agentic AI & Cloud Integration
Location: Chicago, IL - Hybrid (as determined by project requirements)
Employment Type: Full-Time, W2 Payroll Only, 3 + Months contract
Role Overview
We are seeking an innovative Solution Architect to lead the design and delivery of next-generation AI-powered web and mobile applications that combine modern user experiences with autonomous Agentic AI capabilities. This individual will serve as the technical leader responsible for architecting enterprise solutions that seamlessly connect AI agents with cloud platforms, third-party SaaS applications, and complex API ecosystems. Working closely with business stakeholders, engineering teams, and client leadership, the Solution Architect will transform business challenges into scalable, production-ready AI solutions that automate workflows, improve operational efficiency, and accelerate digital transformation. Success in this role requires balancing hands-on technical leadership with strategic architecture, ensuring every solution is secure, resilient, and designed for enterprise scale.
Purpose
This role offers the opportunity to shape how organizations adopt Agentic AI to transform customer experiences and business operations. You will design intelligent systems that move beyond simple automation by enabling AI agents to reason, make decisions, and execute complex business processes across enterprise environments.
You will work at the forefront of enterprise AI, helping define architecture standards for Agentic AI, cloud-native applications, and intelligent automation. The role provides exposure to emerging AI technologies while partnering with executive stakeholders and engineering teams on highly visible transformation initiatives.
This opportunity is ideal for architects who enjoy solving complex technical challenges, building innovative AI solutions, and working directly with clients to deliver measurable business value. You'll influence both technical direction and business strategy while remaining engaged in the delivery of cutting-edge enterprise applications.
Objectives
1. Architect and Deliver Enterprise Agentic AI Solutions
Within the first six months, design and lead the implementation of production-ready web and mobile solutions that leverage Agentic AI workflows to automate business processes and improve customer experiences. Define scalable architectures that integrate AI agents with enterprise systems, cloud platforms, and third-party APIs while ensuring security, reliability, and performance. Success will be measured through successful production deployments, stakeholder adoption, application performance, and measurable business outcomes including automation, reduced manual effort, and improved operational efficiency. This objective may be enhanced using AI-assisted architecture analysis and design tools.
2. Build a Secure, Scalable Cloud Integration Framework
Develop enterprise architecture standards that enable AI agents to securely interact with cloud services and external SaaS platforms using modern API-first integration patterns. Establish governance for authentication, authorization, error handling, monitoring, and resilient communication across distributed systems. Success will be measured through successful integrations, platform stability, security compliance, reduced operational issues, and reusable architectural components. AI-assisted monitoring and API analysis tools should be evaluated where appropriate.
3. Accelerate AI Innovation Through Rapid Prototyping
Within the first 120 days, develop proof-of-concept solutions demonstrating how autonomous AI agents can complete complex, multi-step business processes across cloud environments. Collaborate with business and technical stakeholders to validate concepts, demonstrate business value, and establish implementation roadmaps for enterprise deployment. Success will be measured through prototype delivery, stakeholder engagement, approved implementation plans, and conversion of prototypes into production initiatives.
4. Provide Technical Leadership Across Enterprise AI Programs
Serve as the lead Solution Architect for enterprise AI engagements by translating business objectives into scalable technical solutions, guiding engineering teams through implementation, and communicating architectural strategies to executive and non-technical stakeholders. Lead project estimation, technical planning, risk assessment, and solution governance throughout the software development lifecycle. Success will be measured through delivery quality, stakeholder confidence, project predictability, and successful implementation of enterprise AI initiatives.
Subtasks
Design Enterprise Web and Mobile Solution Architectures
Develop scalable frontend architectures using modern web and mobile technologies that provide intuitive user experiences while serving as the interaction layer for autonomous AI agents. Ensure architectures support long-term scalability, maintainability, and performance.
Architect Agent-to-System Communication
Define secure and resilient communication patterns enabling AI agents to interact with enterprise cloud services, SaaS platforms, and external APIs. Establish standards for authentication, authorization, event handling, retry logic, rate limiting, and fault tolerance.
Develop Agentic AI Proofs of Concept
Rapidly build and demonstrate proof-of-concept solutions illustrating how AI agents can automate complex workflows, manage cloud resources, monitor operational health, and execute business processes with minimal human intervention.
Establish Enterprise Integration Standards
Design reusable API integration frameworks supporting cloud-native architectures, event-driven systems, microservices, and real-time communication across enterprise platforms while ensuring security and governance requirements are consistently applied.
Collaborate with Clients and Cross-Functional Teams
Partner with business leaders, product managers, software engineers, UX designers, and executive stakeholders to define requirements, prioritize initiatives, and ensure technical solutions align with strategic business objectives.
Lead Architecture Governance and Delivery Planning
Provide technical oversight throughout project execution by developing implementation roadmaps, estimating project effort, identifying delivery risks, and guiding engineering teams through successful implementation and deployment.
Continuously Evaluate and Integrate Emerging AI Technologies
Within the first 90–180 days, proactively evaluate emerging AI models, agent frameworks, orchestration platforms, and intelligent automation technologies to identify opportunities that improve solution quality, accelerate delivery, and enhance client outcomes. Lead pilot initiatives and recommend practical innovations that strengthen the organization's enterprise AI capabilities.
Tech Environment
Successful candidates should demonstrate expertise in:
Agentic AI architectures
Large Language Models (LLMs)
LangChain
LlamaIndex
Retrieval-Augmented Generation (RAG)
Multi-Agent Systems
Function Calling
React
Next.js
Flutter or React Native
API-first architecture
Microservices
Event-Driven Architecture
OAuth 2.0 / OpenID Connect
WebSockets
AWS, Azure, or Google Cloud Platform
Enterprise SaaS integrations (Salesforce, Stripe, Twilio, and similar platforms)
Success
Within the first 90-Days, this individual will be recognized as the technical leader who successfully established scalable Agentic AI architecture standards, delivered production-ready AI-powered web and mobile solutions, accelerated enterprise AI adoption through innovative proof-of-concept initiatives, and became the trusted advisor for enterprise AI strategy, cloud integration, and solution architecture.
Location: Chicago, IL - Hybrid (as determined by project requirements)
Employment Type: Full-Time, W2 Payroll Only, 3 + Months contract
Role Overview
We are seeking an innovative Solution Architect to lead the design and delivery of next-generation AI-powered web and mobile applications that combine modern user experiences with autonomous Agentic AI capabilities. This individual will serve as the technical leader responsible for architecting enterprise solutions that seamlessly connect AI agents with cloud platforms, third-party SaaS applications, and complex API ecosystems. Working closely with business stakeholders, engineering teams, and client leadership, the Solution Architect will transform business challenges into scalable, production-ready AI solutions that automate workflows, improve operational efficiency, and accelerate digital transformation. Success in this role requires balancing hands-on technical leadership with strategic architecture, ensuring every solution is secure, resilient, and designed for enterprise scale.
Purpose
This role offers the opportunity to shape how organizations adopt Agentic AI to transform customer experiences and business operations. You will design intelligent systems that move beyond simple automation by enabling AI agents to reason, make decisions, and execute complex business processes across enterprise environments.
You will work at the forefront of enterprise AI, helping define architecture standards for Agentic AI, cloud-native applications, and intelligent automation. The role provides exposure to emerging AI technologies while partnering with executive stakeholders and engineering teams on highly visible transformation initiatives.
This opportunity is ideal for architects who enjoy solving complex technical challenges, building innovative AI solutions, and working directly with clients to deliver measurable business value. You'll influence both technical direction and business strategy while remaining engaged in the delivery of cutting-edge enterprise applications.
Objectives
1. Architect and Deliver Enterprise Agentic AI Solutions
Within the first six months, design and lead the implementation of production-ready web and mobile solutions that leverage Agentic AI workflows to automate business processes and improve customer experiences. Define scalable architectures that integrate AI agents with enterprise systems, cloud platforms, and third-party APIs while ensuring security, reliability, and performance. Success will be measured through successful production deployments, stakeholder adoption, application performance, and measurable business outcomes including automation, reduced manual effort, and improved operational efficiency. This objective may be enhanced using AI-assisted architecture analysis and design tools.
2. Build a Secure, Scalable Cloud Integration Framework
Develop enterprise architecture standards that enable AI agents to securely interact with cloud services and external SaaS platforms using modern API-first integration patterns. Establish governance for authentication, authorization, error handling, monitoring, and resilient communication across distributed systems. Success will be measured through successful integrations, platform stability, security compliance, reduced operational issues, and reusable architectural components. AI-assisted monitoring and API analysis tools should be evaluated where appropriate.
3. Accelerate AI Innovation Through Rapid Prototyping
Within the first 120 days, develop proof-of-concept solutions demonstrating how autonomous AI agents can complete complex, multi-step business processes across cloud environments. Collaborate with business and technical stakeholders to validate concepts, demonstrate business value, and establish implementation roadmaps for enterprise deployment. Success will be measured through prototype delivery, stakeholder engagement, approved implementation plans, and conversion of prototypes into production initiatives.
4. Provide Technical Leadership Across Enterprise AI Programs
Serve as the lead Solution Architect for enterprise AI engagements by translating business objectives into scalable technical solutions, guiding engineering teams through implementation, and communicating architectural strategies to executive and non-technical stakeholders. Lead project estimation, technical planning, risk assessment, and solution governance throughout the software development lifecycle. Success will be measured through delivery quality, stakeholder confidence, project predictability, and successful implementation of enterprise AI initiatives.
Subtasks
Design Enterprise Web and Mobile Solution Architectures
Develop scalable frontend architectures using modern web and mobile technologies that provide intuitive user experiences while serving as the interaction layer for autonomous AI agents. Ensure architectures support long-term scalability, maintainability, and performance.
Architect Agent-to-System Communication
Define secure and resilient communication patterns enabling AI agents to interact with enterprise cloud services, SaaS platforms, and external APIs. Establish standards for authentication, authorization, event handling, retry logic, rate limiting, and fault tolerance.
Develop Agentic AI Proofs of Concept
Rapidly build and demonstrate proof-of-concept solutions illustrating how AI agents can automate complex workflows, manage cloud resources, monitor operational health, and execute business processes with minimal human intervention.
Establish Enterprise Integration Standards
Design reusable API integration frameworks supporting cloud-native architectures, event-driven systems, microservices, and real-time communication across enterprise platforms while ensuring security and governance requirements are consistently applied.
Collaborate with Clients and Cross-Functional Teams
Partner with business leaders, product managers, software engineers, UX designers, and executive stakeholders to define requirements, prioritize initiatives, and ensure technical solutions align with strategic business objectives.
Lead Architecture Governance and Delivery Planning
Provide technical oversight throughout project execution by developing implementation roadmaps, estimating project effort, identifying delivery risks, and guiding engineering teams through successful implementation and deployment.
Continuously Evaluate and Integrate Emerging AI Technologies
Within the first 90–180 days, proactively evaluate emerging AI models, agent frameworks, orchestration platforms, and intelligent automation technologies to identify opportunities that improve solution quality, accelerate delivery, and enhance client outcomes. Lead pilot initiatives and recommend practical innovations that strengthen the organization's enterprise AI capabilities.
Tech Environment
Successful candidates should demonstrate expertise in:
Agentic AI architectures
Large Language Models (LLMs)
LangChain
LlamaIndex
Retrieval-Augmented Generation (RAG)
Multi-Agent Systems
Function Calling
React
Next.js
Flutter or React Native
API-first architecture
Microservices
Event-Driven Architecture
OAuth 2.0 / OpenID Connect
WebSockets
AWS, Azure, or Google Cloud Platform
Enterprise SaaS integrations (Salesforce, Stripe, Twilio, and similar platforms)
Success
Within the first 90-Days, this individual will be recognized as the technical leader who successfully established scalable Agentic AI architecture standards, delivered production-ready AI-powered web and mobile solutions, accelerated enterprise AI adoption through innovative proof-of-concept initiatives, and became the trusted advisor for enterprise AI strategy, cloud integration, and solution architecture.