AI Systems Integration Engineer

Prairie Consulting Services; Chicago (IL); On-site; USD 130,000 - 165,000; Full time

Job summary

Prairie Consulting Services seeks a senior integration engineer to design, build, and support secure integrations between enterprise applications, data sources, and AI platforms. You will deliver reusable connectors, robust error handling, and scalable integration patterns across complex workflows.

Collaborating with product, engineering, security, risk, and architecture teams, you will translate business needs into practical integration designs, maintain documentation, runbooks, and operational

Qualifications

• 7+ years of experience in software/ integration engineering roles.
• Experience designing enterprise-scale integrations via APIs or microservices.
• Hands-on Azure cloud development and deployment experience.
• Production support, incident troubleshooting, and RCA.
• Strong security, access controls, logging, and auditability knowledge.
• Ability to translate business needs into integration designs.
• Experience with Agile or hybrid delivery using Azure DevOps, Jira, ServiceNow, Confluence, SharePoint.
• Strong communication and cross-functional collaboration.

Responsibilities

• Design, develop, test, and support integrations between Digital Coworkers, the GAI Platform, enterprise applications, APIs, data sources, and workflow systems.
• Build reusable services, connectors, and integration patterns across coworker use cases.
• Configure approved tool access, workflow actions, permissions, and orchestration paths for digital coworkers.
• Partner with Product, Engineering, Security, Risk, Architecture, and Application Owner teams for feasibility and sequencing.
• Support RAG and enterprise knowledge access by integrating data sources into AI workflows.
• Create and maintain technical documentation, interface specs, test evidence, deployment notes, runbooks, and run readiness materials.
• Troubleshoot integration issues, analyze production defects, support incident response, and remediation actions.
• Contribute to backlog, planning, release readiness, and status updates for integration workstreams.
• Identify opportunities to improve repeatability, security, monitoring, and delivery time.

Skills

Enterprise integration

Azure cloud

APIs & microservices

Incident troubleshooting

Documentation

Agile collaboration

Security controls

Tools

Azure DevOps

Jira

Confluence

ServiceNow

SharePoint

Job description

Digital Coworkers program by designing, building, and supporting secure integrations between digital coworkers, enterprise applications, APIs, workflow systems, knowledge repositories, and approved data sources.

Experience Level

Senior individual contributor with enterprise integration engineering, software engineering, platform engineering, cloud services, automation, and production support experience.

Primary Focus

API integration, tool connectivity, data and knowledge access patterns, RAG enablement, agent workflow integration, operational readiness, production troubleshooting, documentation, and reusable integration patterns.

Engagement Partners

Product Leads, Engineering Leads, AI Engineers, Platform Operations, Enterprise Architecture, Application Owners, Information Security, Risk, and business stakeholders.

Integration designs, services, APIs, connectors, technical documentation, runbooks, release artifacts, test evidence, operational readiness materials, reusable patterns, issue triage notes, and implementation plans, integration code to support agentic workflows

Qualifications (Must Haves)

• 7+ years of experience in software engineering, integration engineering, platform engineering, cloud engineering, or similar enterprise technology roles.
• Experience designing and implementing enterprise-scale integrations using APIs, services, event-driven patterns, or microservices.
• Hands-on experience with cloud-native development and deployment patterns, preferably Microsoft Azure.
• Experience supporting production technology platforms, including incident troubleshooting, root cause analysis, monitoring, and operational documentation.
• Strong understanding of secure connectivity, identity and access controls, data protection, logging, auditability, and enterprise control environments.
• Ability to translate business workflow needs into practical technical integration designs and delivery artifacts.
• Experience working in Agile or hybrid delivery environments using tools such as Azure DevOps, Jira, ServiceNow, Confluence, SharePoint, or similar platforms.
• Strong communication and documentation skills with the ability to work across product, engineering, architecture, security, risk, and business stakeholder groups.

Preferred Qualifications

• Experience in financial services, regulated technology environments, enterprise risk and control frameworks, or AI governance review processes.
• Working knowledge of Generative AI, LLM concepts, Retrieval Augmented Generation (RAG), agent workflows, prompt engineering, responsible AI, AI observability, and model monitoring.
• Experience integrating structured and unstructured enterprise data sources such as SharePoint, ServiceNow, Snowflake, Databricks, Fabric, document repositories, or operational platforms.
• Experience creating reusable connector patterns, platform enablement documentation, test plans, release notes, runbooks, and support model inputs.

Required Technical Skills

Generative AI concepts, LLM concepts, digital coworkers, AI agents, RAG patterns, agent workflows, model access, guardrails, responsible AI controls, platform onboarding, observability, and telemetry.

Integration Engineering

REST APIs, service integrations, event-driven architecture, microservices, API gateways, authentication patterns, error handling, retry logic, integration testing, and reusable connector design.

Data / Knowledge

SQL, structured and unstructured data integration, SharePoint, Microsoft Graph, Snowflake, Databricks, Fabric, knowledge repositories, data access controls, and retrieval optimization.

Tools / Reporting

Azure DevOps, Jira, ServiceNow, Confluence, SharePoint, Power BI, Excel, technical documentation repositories, runbooks, dashboards, and structured status reporting. Prompt coding.

Cross-functional coordination, dependency management, security review support, risk documentation, operational readiness, vendor handoff materials, production support, and governance artifacts.

Tasks & Responsibilities

• Design, develop, test, and support integrations between Digital Coworkers, the GAI Platform, enterprise applications, APIs, data sources, and workflow systems.
• Build reusable services, connectors, and integration patterns that can be applied across multiple digital coworker use cases.
• Configure approved tool access, workflow actions, permissions, and orchestration paths needed for digital coworkers to execute defined business processes.
• Partner with Product, Engineering, Security, Risk, Architecture, and Application Owner teams to confirm feasibility, access models, controls, dependencies, and implementation sequencing.
• Support RAG and enterprise knowledge access patterns by integrating approved structured and unstructured data sources into AI workflows.
• Create and maintain technical documentation, interface specifications, test evidence, deployment notes, support runbooks, decision records, and operational readiness materials.
• Troubleshoot integration issues, analyze production defects, support incident response, and recommend durable remediation actions.
• Contribute to backlog refinement, sprint planning, release readiness, implementation planning, dependency tracking, and status updates for assigned integration workstreams.
• Identify opportunities to improve repeatability, security, monitoring, documentation quality, and time-to-delivery for future digital coworker integrations.

Success Measures

• Secure integrations delivered with clear documentation, test evidence, and operational support materials.
• Reusable connector and integration patterns that reduce repeated engineering effort across digital coworker implementations.
• Improved speed and consistency of Digital Coworker onboarding into approved enterprise systems and data sources.
• Reduced integration defects, clearer incident triage paths, and stronger production support readiness.