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Mechanical Integration Engineer Jobs in Chicago, IL

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Mechanical Integration Engineer information

See Chicago, IL salary details

$46.9K

$106K

$171.5K

How much do mechanical integration engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for mechanical integration engineer in Chicago, IL is $105,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $130,300.00 per year, depending on experience, location, and employer.

What are some common challenges a mechanical integration engineer faces when coordinating with cross-functional teams during a project?

Mechanical Integration Engineers often work closely with electrical, software, and manufacturing teams to ensure all components fit and function together seamlessly. One common challenge is aligning differing timelines, priorities, and technical requirements between teams, which can lead to integration delays or design conflicts. Strong communication and project management skills are crucial to proactively identify potential issues and facilitate effective collaboration. Being adaptable and solution-oriented helps in navigating these complexities to deliver a successful integrated product.

What are the key skills and qualifications needed to thrive as a mechanical integration engineer, and why are they important?

To thrive as a Mechanical Integration Engineer, you need a solid background in mechanical engineering principles, systems integration, and typically a bachelor's degree in mechanical or aerospace engineering. Familiarity with CAD software (such as SolidWorks or CATIA), product lifecycle management (PLM) systems, and relevant industry certifications are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills make a candidate stand out in this role. These competencies are crucial for ensuring that complex mechanical systems are seamlessly integrated and function reliably within larger projects.

What is the difference between Mechanical Integration Engineer vs Mechanical Design Engineer?

AspectMechanical Integration EngineerMechanical Design Engineer
Primary FocusIntegrating mechanical components into systems, ensuring compatibility and functionalityCreating and developing mechanical components and assemblies from concepts
Skills & CertificationsCAD, system integration, testing, often requires engineering degreeCAD, design software, prototyping, often requires engineering degree
Work EnvironmentSystems integration labs, manufacturing facilities, cross-disciplinary teamsDesign studios, R&D labs, manufacturing settings
Industry UsageAerospace, automotive, robotics, where system integration is keyProduct development, consumer electronics, machinery design

While both roles require engineering backgrounds and CAD skills, Mechanical Integration Engineers focus on combining mechanical components into complete systems, ensuring they work seamlessly. Mechanical Design Engineers primarily develop individual components and assemblies. Both roles are essential in product development but differ in their core responsibilities and focus areas.

What are popular job titles related to Mechanical Integration Engineer jobs in Chicago, IL?

For Mechanical Integration Engineer jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Mechanical Integration Engineer jobs in Chicago, IL look for?

The top searched job categories for Mechanical Integration Engineer jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Mechanical Integration Engineer jobs?

Cities near Chicago, IL with the most Mechanical Integration Engineer job openings:

Mechanical Integration Engineer jobs near you
Infographic showing various Mechanical Integration Engineer job openings in Chicago, IL as of August 2026, with employment types broken down into 89% Full Time, 9% Part Time, 1% Contract, and 1% Nights. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $105,979 per year, or $51 per hour.

AI SYSTEM INTEGRATION ENGINEER

Judge Group, Inc.

Chicago, IL • On-site

$80 - $100/hr

Other

Posted 11 days ago

Job description

Location: Chicago, IL Salary: $80.00 USD Hourly - $100.00 USD Hourly Description: Title: AI System Integration Engineer
Job Summary
We are seeking a Senior AI Integration Engineer to design, develop, and support enterprise-grade integrations that connect AI-powered digital coworkers, Generative AI platforms, business applications, data sources, and workflow systems. The ideal candidate will bring strong expertise in cloud-native engineering, enterprise integrations, AI technologies, and production platform support.
This role will collaborate closely with Product, Engineering, Architecture, Security, Risk, and Business stakeholders to build scalable, secure, and reusable integration patterns that accelerate AI adoption across the organization.
Key Responsibilities
  • Design, develop, test, deploy, and maintain integrations between AI solutions, enterprise applications, APIs, workflow platforms, and data sources.
  • Build reusable services, connectors, and integration frameworks that support multiple AI and digital coworker use cases.
  • Develop and implement API-driven, event-driven, and microservices-based integration architectures.
  • Support Retrieval-Augmented Generation (RAG) and enterprise knowledge management solutions by integrating structured and unstructured data sources.
  • Configure workflow orchestration, permissions, tool access, and governance controls for AI agents and digital coworkers.
  • Collaborate with Product, Security, Risk, Architecture, and Application teams to validate technical feasibility, dependencies, access requirements, and implementation strategies.
  • Troubleshoot production issues, perform root cause analysis, and implement sustainable remediation solutions.
  • Contribute to sprint planning, backlog refinement, release management, dependency tracking, and project status reporting.
  • Create and maintain technical documentation, interface specifications, test plans, deployment guides, operational runbooks, and support materials.
  • Continuously improve integration standards, monitoring capabilities, security controls, and delivery processes.

Required Qualifications
  • 5+ years of experience in Software Engineering, Integration Engineering, Platform Engineering, Cloud Engineering, or related technology roles.
  • Proven experience designing and implementing enterprise-scale integrations using APIs, microservices, event-driven architectures, and service-based platforms.
  • Hands-on experience with cloud-native development and deployment, preferably on Microsoft Azure.
  • Strong experience supporting production platforms, including monitoring, troubleshooting, incident management, and root cause analysis.
  • Understanding of enterprise security principles including authentication, authorization, identity management, data protection, logging, and audit controls.
  • Experience translating business requirements into practical technical solutions and architecture designs.
  • Experience working within Agile delivery environments using tools such as Azure DevOps, Jira, ServiceNow, Confluence, and SharePoint.
  • Strong communication, stakeholder management, and technical documentation skills.

Preferred Qualifications
  • Experience working in financial services, regulated industries, enterprise governance, risk management, or AI compliance environments.
  • Working knowledge of:
    • Generative AI
    • Large Language Models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • AI Agents and Agentic Workflows
    • Prompt Engineering
    • Responsible AI and AI Governance
    • AI Observability and Model Monitoring
  • Experience with:
    • Azure OpenAI
    • Azure API Management
    • Azure Functions
    • Azure Kubernetes Service (AKS)
    • Microsoft Graph
    • Copilot Studio
    • LangChain
    • LangGraph
    • Model Context Protocol (MCP)
  • Experience integrating enterprise platforms such as SharePoint, ServiceNow, Snowflake, Databricks, Microsoft Fabric, document repositories, and operational systems.
  • Experience creating reusable connector frameworks, deployment documentation, test strategies, release notes, and operational runbooks.

Required Technical Skills
AI & Agentic Platforms
  • Generative AI and LLM concepts
  • AI Agents and Agentic Frameworks
  • RAG and Hybrid RAG architectures
  • Prompt Engineering
  • MCP (Model Context Protocol)
  • Responsible AI and Governance Controls
  • AI Observability, Monitoring, and Telemetry
  • LangChain and LangGraph

Integration Engineering
  • REST APIs
  • Service-Oriented Architecture
  • Event-Driven Architecture
  • Microservices Design
  • API Gateway Management
  • Authentication and Authorization Patterns
  • Integration Testing
  • Error Handling and Retry Mechanisms
  • Reusable Connector Development

Cloud & DevOps
  • Microsoft Azure
  • Azure Functions
  • Azure API Management (APIM)
  • Azure Kubernetes Service (AKS)
  • Azure DevOps
  • CI/CD Pipelines
  • Infrastructure-as-Code Concepts
  • Monitoring and Logging
  • Release and Environment Management

Data & Analytics
  • Python
  • SQL
  • Kafka
  • Snowflake
  • Databricks
  • Microsoft Fabric
  • Structured and Unstructured Data Integration
  • Knowledge Repository Management
  • Data Access Controls
  • Retrieval Optimization

Tools & Reporting
  • Azure DevOps
  • Jira
  • ServiceNow
  • Confluence
  • SharePoint
  • Power BI
  • Excel
  • Technical Documentation Platforms
  • Operational Runbooks and Dashboards

Enterprise Delivery
  • Cross-functional Collaboration
  • Dependency Management
  • Security and Risk Review Support
  • Governance Documentation
  • Vendor Coordination
  • Production Support Readiness
  • Release Planning and Change Management

Success Measures
  • Delivery of secure, scalable, and well-documented enterprise integrations.
  • Development of reusable integration and connector frameworks that improve engineering efficiency.
  • Faster onboarding of AI solutions and digital coworkers into enterprise systems and data platforms.
  • Reduction in production defects and improvement in incident response readiness.
  • High-quality technical documentation, operational support assets, and governance compliance artifacts.

Technical Skills (Mandatory)
  • LangChain / LangGraph Tool Stack
  • Python
  • Kafka
  • Snowflake
  • Databricks
  • Azure Cloud Services
  • REST APIs & Integration Engineering
  • Generative AI & RAG Frameworks
  • MCP and AI Agent Frameworks
  • Azure DevOps & CI/CD Pipelines

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