Architect, Delivery Operations & AI Systems
AbbVie
July 03, 2026
Remote friendly (North Chicago, IL)
United States
$109,500 - $208,500 USD yearly
IT
Responsibilities:
- Architect enterprise delivery solutions for complex business and scientific workflows, including software platforms, automation pipelines, integrations, and AI-enabled operational capabilities.
- Define end-to-end architecture patterns for agentic and traditional systems (orchestration, tool integration, event-driven services, APIs, cloud-native components, enterprise data connectivity).
- Lead design of LLM/agent capabilities: prompting/orchestration, memory/context handling, RAG, Model Context Protocol (MCP) structures, and human-in-the-loop pathways.
- Establish architecture guardrails for safety, security, compliance, observability, reliability, and cost management across AI and application delivery.
- Provide senior technical consultation on architecture decisions, technology selection, and tradeoffs.
- Design for operational resilience (monitoring/telemetry, fallback, access control, prompt-injection protection, service recovery).
- Drive cloud, DevOps, and MLOps standards (CI/CD, containerization, serverless, message-based processing, scalable runtimes).
- Evaluate emerging technologies and translate to pragmatic architecture recommendations.
- Lead cross-functional architecture alignment and mentor engineers/tech leads.
Qualifications:
Required:
- BS + 7 years; or MS + 6 years; or PhD + 2 years in relevant field.
- Experience in software/enterprise/solution/app-platform delivery.
- Experience with AI/LLM-enabled systems, agent orchestration, RAG, or secure enterprise AI architecture.
- Demonstrated large-scale enterprise architecture design/implementation.
- Strong cloud-native, APIs, distributed systems, event-driven design, and delivery practices.
- Strong software SDLC (Traditional/Agile), operational support, and platform reliability.
- Regulated-environment experience applying security/compliance/data governance.
- Evaluate emerging tech into scalable solutions; excellent communication.
Preferred:
- Life sciences/R&D/Safety domain experience.
- DevSecOps/CI-CD and hands-on Azure; familiarity with Claude, Jira, Confluent, Docker, Git, JFrog, Tricentis (qTest/Tosca), ServiceNow, Azure DevOps.
- Agentic methodologies (e.g., BMAD).
Benefits (explicitly stated):
- Paid time off; medical/dental/vision insurance; 401(k); long-term incentive program eligibility.
- Architect enterprise delivery solutions for complex business and scientific workflows, including software platforms, automation pipelines, integrations, and AI-enabled operational capabilities.
- Define end-to-end architecture patterns for agentic and traditional systems (orchestration, tool integration, event-driven services, APIs, cloud-native components, enterprise data connectivity).
- Lead design of LLM/agent capabilities: prompting/orchestration, memory/context handling, RAG, Model Context Protocol (MCP) structures, and human-in-the-loop pathways.
- Establish architecture guardrails for safety, security, compliance, observability, reliability, and cost management across AI and application delivery.
- Provide senior technical consultation on architecture decisions, technology selection, and tradeoffs.
- Design for operational resilience (monitoring/telemetry, fallback, access control, prompt-injection protection, service recovery).
- Drive cloud, DevOps, and MLOps standards (CI/CD, containerization, serverless, message-based processing, scalable runtimes).
- Evaluate emerging technologies and translate to pragmatic architecture recommendations.
- Lead cross-functional architecture alignment and mentor engineers/tech leads.
Qualifications:
Required:
- BS + 7 years; or MS + 6 years; or PhD + 2 years in relevant field.
- Experience in software/enterprise/solution/app-platform delivery.
- Experience with AI/LLM-enabled systems, agent orchestration, RAG, or secure enterprise AI architecture.
- Demonstrated large-scale enterprise architecture design/implementation.
- Strong cloud-native, APIs, distributed systems, event-driven design, and delivery practices.
- Strong software SDLC (Traditional/Agile), operational support, and platform reliability.
- Regulated-environment experience applying security/compliance/data governance.
- Evaluate emerging tech into scalable solutions; excellent communication.
Preferred:
- Life sciences/R&D/Safety domain experience.
- DevSecOps/CI-CD and hands-on Azure; familiarity with Claude, Jira, Confluent, Docker, Git, JFrog, Tricentis (qTest/Tosca), ServiceNow, Azure DevOps.
- Agentic methodologies (e.g., BMAD).
Benefits (explicitly stated):
- Paid time off; medical/dental/vision insurance; 401(k); long-term incentive program eligibility.