Lead DevOps/Platform Engineer IV - Richland, WA

Job summary

PNNL is seeking a Lead DevOps/Platform Engineer to contribute to advanced AI engineering initiatives, focusing on next-generation systems like agentic AI platforms, large-scale data orchestration, and real-time intelligence processing. This role involves applying expertise in scalable system design and AI/ML engineering to build mission-critical capabilities, while also developing technical leadership and mentoring junior team members.

Benefits

Qualifications

• PhD and 3 years of Software Engineering experience
• MS/MA and 5 years of Software Engineering experience
• BS/BA and 7 years of Software Engineering experience
• AA and 16 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development
• HS/GED and 18 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development
• Degree in computer science, software engineering, or a related field
• Track record of architecting and operating large-scale infrastructure supporting significant user bases, high-volume transaction systems, petabyte-scale data platforms, or production ML systems serving millions of predictions
• Experience building and leading high-performing platform engineering, DevOps, or MLOps teams through hiring, mentoring, technical guidance, and career development
• Experience establishing infrastructure practices, platform strategies, MLOps frameworks, and DevOps transformation initiatives at organizational scale
• Background in mission-critical, regulated, or high-security environments (government, defense, financial services, healthcare) with understanding of compliance requirements for both traditional systems and ML/AI applications
• Demonstrated success leading complex, multi-team infrastructure and MLOps initiatives from architecture through production deployment, operational handoff, and continuous improvement
• Expert-level proficiency in Python and at least one additional language (Go, C#/.NET, C++)
• Proven ability to establish infrastructure automation standards, architect scalable tooling platforms, and guide teams in developing sophisticated automation frameworks
• Mastery of Infrastructure as Code principles with deep expertise in Terraform, CloudFormation, Pulumi, or ARM templates
• Demonstrated ability to design enterprise-wide IaC strategies, module libraries, and governance frameworks
• Proven track record of architecting and leading implementation of enterprise-grade CI/CD platforms
• Ability to define build/release strategies, establish deployment patterns, and drive continuous delivery adoption
• Experience designing internal developer platforms that abstract complexity and accelerate team velocity
• Expert proficiency with GitOps methodologies (ArgoCD, Flux), infrastructure testing frameworks (Terratest, InSpec), and policy-as-code (OPA, Sentinel)
• Strategic application of AI assist tools to drive team productivity, accelerate automation development, and optimize operational efficiency

Responsibilities

• Contribute to next-generation systems including agentic AI platforms, large-scale data orchestration, and real-time intelligence processing
• Apply expertise in scalable system design and AI/ML engineering to build mission-critical capabilities
• Develop technical leadership and establish as a key contributor to the engineering community
• Design and deploy scalable agentic AI systems with dynamic reasoning and decision-making capabilities
• Architect LLM orchestration frameworks using LangChain, LlamaIndex, and emerging agent platforms
• Build MLOps platforms spanning experiment tracking, model versioning, deployment, and governance
• Develop developer-focused tooling, adapters, and interfaces for AI-native frameworks
• Integrate multi-modal data sources (text, vision, structured/sensor data) into cohesive reasoning pipelines
• Design microservices architectures coordinating across multiple domains and security enclaves
• Lead distributed system design processing data from hundreds of sources simultaneously
• Architect real-time streaming platforms handling terabytes per hour with event-driven architectures
• Build robust data pipelines for petabyte-scale ETL, data lake/mesh architectures, and real-time analytics
• Design container orchestration (Kubernetes) and CI/CD pipelines for classified and edge environments
• Deploy AI systems in highly secure environments with resilient agent-to-agent communications
• Create monitoring and observability systems (logging, metrics, tracing) across secure enclaves
• Ensure compliance with ethical AI standards and security-first DevOps practices
• Build geospatial processing, time-series, and intelligence data fusion capabilities
• Lead a team of engineers to deliver on high-risk, high-impact ambiguous technical scope
• Drive technical strategy and architectural decisions across cross-functional teams
• Translate ambiguous requirements and cutting-edge research into actionable technical roadmaps

Skills

Degrees

Security clearance

Relocation