AI Workflow Architect for Enterprise Automation

Daimler Truck North America

Portland (OR)

Hybrid

USD 117,000 - 150,000

Full time

14 days+

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Benefits offered by this job

Annual bonus program

401k matching up to 6%

Non-elective company contribution 3–7%

4 weeks paid vacation

13+ calendar holidays

8 weeks paid parental leave

Employee assistance program

Comprehensive healthcare plans

Onsite fitness (at some locations)

Tuition assistance

Volunteer paid time off

Short-term disability

Long-term disability

Job summary

Daimler Truck North America is seeking a Software Architect focused on AI-enabled workflow architecture to define scalable automation platforms and enterprise integrations. You will design building blocks for workflow execution, model serving, tool integration, data exchange, and observability while collaborating across product, platform, validation, and software engineering teams.

The role operates within the Software Verification and Release organization, supporting global vehicle platforms

Qualifications

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or related field; advanced degree preferred
8+ years of relevant experience in software architecture, distributed systems, enterprise application development, automation platforms, or engineering software systems
Strong programming and software design experience in modern languages such as Python, Java, C#, TypeScript, C/C++, or similar
Experience designing modular, maintainable, and scalable software components for workflow platforms, orchestration frameworks, enterprise integrations, or cloud-native systems
Understanding of AI-enabled software systems, including agentic workflows, model-serving patterns, prompt/tool orchestration, retrieval-augmented generation, evaluation, and governance
Experience with API design, event-driven architecture, microservices, data pipelines, CI/CD, infrastructure as code, observability, secure development, and production operations
Ability to integrate heterogeneous systems through REST APIs, event streams, workflow engines, data services, and enterprise integration patterns
Familiarity with software lifecycle, requirements management, test management, DevOps, release management, traceability, and quality practices in engineering environments
Strong analytical and communication skills with the ability to translate ambiguous business needs into clear architecture decisions and implementation guidance

Responsibilities

Define reference architectures for AI-enabled workflow platforms, agent orchestration, automation pipelines, and enterprise engineering integrations
Design scalable software building blocks for workflow execution, model serving, tool integration, data exchange, observability, and lifecycle management
Develop architecture patterns that combine deterministic automation pipelines with AI-driven agents, human-in-the-loop review gates, and traceable decision points
Collaborate with product owners, software engineers, system engineers, data scientists, and platform teams to translate business needs into robust technical designs
Establish API-first, event-driven, and cloud-native integration approaches across engineering toolchains, enterprise systems, and automation services
Apply software engineering best practices including architecture governance, coding standards, source control, security, CI/CD, automated validation, and operational monitoring
Evaluate emerging AI, automation, and platform technologies and shape technical roadmaps for reusable workflow architecture capabilities
Analyze and design large-scale, distributed, and complex systems with a focus on maintainability, interoperability, reliability, security, scalability, and operational excellence
Provide technical leadership, mentoring, and architectural guidance to implementation teams working on AI-enabled workflows and engineering automation platforms