AI Platform Engineer II — Cloud & Data Pipelines

Pacific Northwest National Laboratory; Richland (WA); On-site; USD 109,000 - 164,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Telehealth care

Mental health benefits

Pension plan

401(k) match

Vacation hours

Job summary

Pacific Northwest National Laboratory (PNNL) is seeking a DevOps/Platform Engineer to join its AI engineering team in Richland, WA or Seattle, WA. You will build scalable AI platforms, cloud-native infrastructure, and high-performance data pipelines to enable real-time intelligence and advanced ML solutions.

The role focuses on AI/ML infrastructure, cloud technologies, and distributed systems while collaborating with researchers and software engineers.

Qualifications

• PhD or MS/MA or BS with two years of professional software development experience.
• Hands-on Python development experience.
• Experience with cloud platforms, infrastructure automation, or CI/CD.
• Exposure to AI/ML workflows, data pipelines, or model deployment.

Responsibilities

• Build and deploy cloud-native AI platforms, agentic AI applications, and LLM solutions.
• Develop scalable data pipelines, streaming architectures, APIs, and microservices.
• Design and maintain containerized infrastructure, CI/CD pipelines, and automated testing.
• Improve system performance, observability, security, and reliability across production environments.
• Collaborate with engineers and researchers to deliver AI capabilities.

Skills

Python

Cloud platforms

CI/CD

Docker

Kubernetes

AI/ML workflows

Data pipelines

Education

PhD

MS/MA

BS/BA + 2 years dev experience

CS/SE degree

Tools

None specified in text

Job description

Pacific Northwest National Laboratory (PNNL) is seeking a DevOps/Platform Engineer to join its AI engineering team in Richland, WA or Seattle, WA. You will build scalable AI platforms, cloud-native infrastructure, and high-performance data pipelines to enable real-time intelligence and advanced ML solutions.

The role focuses on AI/ML infrastructure, cloud technologies, and distributed systems while collaborating with researchers and software engineers.