AI Integration Engineer

Grant Thornton is building an AI Factory to deliver enterprise-grade agentic solutions that generate measurable business outcomes while meeting expectations for trust, auditability, and operational reliability. As an Automation Engineer, you will be the specialist who turns “AI reasoning” into real work executed in systems by designing and implementing workflow automation, integrations, event-driven orchestration, and robust exception handling. You will work as a core member of a cross-functional AI Pod (alongside the AI Product Lead, Lead AI Architect, and AI Engineer(s). Your work ensures agents can safely act, route cases, create records, trigger approvals, and integrate with line-of-business systems while maintaining the controls required in enterprise environments.

Workflow Orchestration & Automation

• Design and implement automated workflows that embed agentic capabilities into real business processes (intake → triage → execution → validation → escalation).
• Build durable orchestration patterns (scheduled, event-driven, stateful workflows) that support multi-step, long-running business processes.
• Implement exception handling patterns (retries, dead-letter queues, compensating actions) to ensure reliability.

Integration Engineering (Systems + Tools)

• Build integration between AI solutions and enterprise systems (e.g., CRM, ERP, case management, ticketing, document management).
• Develop and maintain API connections, connectors, and integration services.
• Implement tool interfaces that agents can safely call (e.g., “create case,” “update record,” “submit request,” “generate document,” “route for approval”).

Human-in-the-Loop Controls & Guardrails

• Implement human review and approval workflows where required (e.g., high-risk decisions, financial actions, customer communications).
• Create escalation paths and safe fallback mechanisms (e.g., route to queue, assign to human, log and halt).
• Ensure auditability: consistent logging of actions, inputs, approvals, outcomes, and exceptions.

Reliability, Observability & Operations

• Instrument workflows for operational monitoring (latency, failure rates, throughput, SLA/SLO adherence).
• Provide runbooks and operational documentation for deployed automations.
• Support production troubleshooting, incident response, and iterative improvement.

Collaboration in the AI Pod

• Partner with the Lead AI Architect to align automation design to the overall agentic architecture and security model.
• Work with AI Engineers to implement safe tool-calling patterns and data exchange contracts.

Collaborate with AI Product Leads to define acceptance criteria, SLAs, and adoption requirements

Experience

• 5+ years of experience in automation engineering, integration engineering, or workflow orchestration.
• Proven track record delivering production automations that integrate multiple systems and support real business operations.
• Experience working in agile delivery teams and cross-functional pods.

Technical Skills

• Strong experience designing and implementing:
• APIs (REST/GraphQL), webhooks, and message-based patterns
• Workflow engines and orchestration patterns (state machines, queues, events)
• Authentication/authorization patterns (OAuth, managed identities, service principals)
• Proficiency in at least one general-purpose language (e.g., Python, TypeScript/JavaScript, C#, Java) for building services and integrations.

Operational & Enterprise Readiness

• Understanding of enterprise non-functional requirements:
• Security, privacy, access controls
• Audit logging and traceability
• Reliability, retry logic, and idempotency
• Performance and scalability considerations

Preferred Qualifications

• Hands-on experience with Microsoft ecosystem automation and integration, such as:
• Power Automate, Logic Apps, Azure Functions, API Management, Service Bus/Event Grid
• Experience integrating with common enterprise platforms (examples):
• Dynamics 365 / Salesforce, ServiceNow, SAP/Oracle, Workday, SharePoint/OneDrive, email/chat channels
• Experience implementing:
• Human-in-the-loop patterns and approval workflows
• Document generation, ingestion, and routing (IDP/Document AI adjacent)
• Consulting or client-facing delivery experience in complex enterprise environments

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