Super Intelligence Platform Integration Engineer

LLNL•Livermore, CA

18h•$121,830 - $185,544•Hybrid

About The Position

Lawrence Livermore National Laboratory is seeking a Super Intelligence (SI) Platform Integration Engineer in the Materials Engineering Division within the Engineering Directorate. The role builds and supports the shared services, integration, and automation layer connecting SI applications with internal systems, documented equipment interfaces, and approved external services. It spans backend services, integration tooling, and operations, supporting reliable and secure SI systems using established deployment and operational practices. The position offers a hybrid schedule, with in-person and virtual work and the flexibility to work from home one or more days per week. It may be filled at either the SES.1 or SES.2 level based on knowledge and related experience. SES.2 responsibilities include designing integrations across multiple services and providing informal technical guidance. This is a Career Indefinite position open to Lab employees and external candidates, and it requires eligibility for a U.S. DOE Q-level security clearance.

Requirements

Ability to secure and maintain a U.S. DOE Q-level security clearance; U.S. citizenship is required.
Bachelor’s degree in computer science, software engineering, or a related field, or an equivalent combination of education and related experience.
Experience through coursework, projects, research, internships, or professional work building or supporting backend services, internal platforms, DevOps workflows, or integration tooling.
Proficiency in Go, Rust, or Python for automation, service integration, and operational tooling.
Familiarity with APIs, webhooks, queues, and event-driven systems.
Working knowledge of Linux, containers, CI/CD, and cloud-hosted services.
Basic networking knowledge, including service connectivity, ports, DNS, proxies, TLS, authentication, and firewall-aware troubleshooting.
At the SES.2 level, ability to independently design, implement, and troubleshoot integrations spanning APIs, event-driven systems, and secure service operations.
At the SES.2 level, ability to improve the reliability or security of shared service integrations through reusable tooling, observability, or operational controls.

Nice To Haves

Experience with observability tools for logging, metrics, tracing, and alerting.
Familiarity with Kubernetes, Docker Compose, Terraform, or other infrastructure automation tools.
Exposure to identity and access patterns such as OAuth, service accounts, and RBAC.
Experience supporting machine learning or LLM-based applications in production environments.

Responsibilities

Build and maintain reusable service frameworks, integration adapters, and automation components that enable agent-facing tools to connect securely to internal and approved external systems.
Integrate APIs, webhooks, queues, and event-driven services into reliable integrations supporting agent-driven workflows.
Provide shared connectivity among agent services, hardware gateways, internal platforms, and approved third-party systems.
Implement and improve deployment workflows, secrets management, monitoring, logging, and operational reliability for agent-facing services within established organizational systems.
Help define and implement permission boundaries, auditability, rate limiting, and fallback behaviors for automated actions.
Partner with embedded, applied physical SI, security, and application engineers to troubleshoot issues and improve integration reliability; coordinate with organizational cybersecurity partners on new approaches with support from senior engineers.
Perform other duties as assigned.
At the SES.2 level, design integration approaches spanning multiple services, queues, hardware gateways, and approved third-party APIs.
At the SES.2 level, improve shared platform capabilities through reusable adapters, stronger observability, and safer operational controls based on operational experience.
At the SES.2 level, coordinate technical decisions with embedded, applied physical SI, security, and application teams, including adopting new integration approaches with cybersecurity partners, and provide informal technical guidance to less experienced engineers.