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Principal Engineer

Job in Chicago, Cook County, Illinois, 60601, USA
Listing for: Georgia IT, Inc.
Full Time position
Listed on 2026-09-01
Job specializations:
  • Software Development
    Software Architect, AI Engineer (Applied/Software)
Job Description & How to Apply Below

Principal Engineer, Business Process & AI Automation

Location:

Hybrid (New York, Chicago, Dallas) Engagement Type:
Contract-to-Hire

Job Summary:

Looking for a Principal Engineer with a strong penchant for business process, someone equally comfortable in a systems architecture review and a stakeholder workshop. This isn't a business-analyst role dressed up in an engineering title; we need someone with real architecture-level engineering depth (integration patterns, data architecture, system-of-record design, API/event architecture) who chooses to point that skill set at messy, disjointed business processes and figure out where AI and automation can be embedded without breaking the systems underneath them.

This is a contract engagement: you'll own the technical design of how automation and AI interface with our line-of-business (LoB) systems, define the target-state data architecture that makes that possible, and be the technical authority stakeholders and the engineering org both trust to get the integration right, not just diagram it.

Key Responsibilities
  • Design the technical architecture for how AI/automation components (agents, RPA, workflow engines, LLM-based services) integrate with core LoB systems, including CRM, ERP, finance, property/asset management, and other domain platforms, covering system-of-record decisions, API contracts, event schemas, and middleware/integration layer design.
  • Work directly with business stakeholders to reverse-engineer current-state processes that span disconnected systems and teams. Model them formally (BPMN, value-stream maps) and translate them into technical requirements and system interaction diagrams, not just narrative process maps.
  • Trace and document data lineage across systems, including sources of truth, transformation points, latency, duplication, and quality issues. Design target-state data flows (batch, event-streaming, real-time API) that support reliable automation and are resilient to the realities of legacy LoB systems.
  • Define and enforce integration standards (API design, auth/security patterns, data contracts, versioning) across automation initiatives so point solutions don't calcify into new technical debt.
  • Assess where AI genuinely fits (classification, extraction, agentic workflows, prediction) versus where deterministic automation (RPA, rules engines, iPaaS) is the right tool, and design the technical pattern, including error handling, human-in-the-loop checkpoints, and observability.
  • Act as the technical counterpart in business workshops, translating business pain points into architecture decisions in real time, and translating architecture trade-offs back into terms business stakeholders can decide on.
  • Evaluate vendor/platform options (iPaaS, RPA platforms, LLM/agent frameworks) against the actual technical constraints of our LoB systems, and make build/buy/integrate recommendations with supporting architecture rationale
  • Produce a phased technical roadmap for automation/AI rollout that accounts for system dependencies, data readiness, and integration risk, not just business priority.
Basic Qualifications
  • 8+ years in a senior/staff/principal engineering role, with direct ownership of integration architecture, data architecture, or platform architecture in a multi-system environment.
  • Demonstrated fluency in integration patterns: REST/GraphQL APIs, event-driven architecture (Kafka, Event Bridge, etc.), ETL/ELT, iPaaS (Mule Soft, Boomi, Workato), and message-oriented middleware.
  • Real experience designing data architecture: data models, data lineage, master data management, and system-of-record decisions across disparate LoB platforms.
  • Working technical knowledge of AI/automation implementation. Not vendor buzzwords, but an understanding of where LLM-based agents, RPA, and rules engines actually sit in a technical stack, their failure modes, and their integration requirements.
  • Proven ability to formally model business processes (BPMN 2.0 or equivalent) and convert them into technical specifications engineering can build from.
  • Strong grasp of enterprise architecture frameworks (TOGAF or equivalent), comfortable producing current-state/target-state…
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