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Clarity Innovations is seeking a Platform Engineering Architect to develop AI capabilities and enhance our innovative solutions for national security. This role emphasizes operationalizing AI, with responsibilities in Kubernetes management and AI infrastructure development.
The ideal candidate will possess extensive experience in DevSecOps and be skilled in software development, Kubernetes, and cloud architectures. Join us in a dynamic environment that values innovation and personal growth.
Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world.
Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact.
We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security.
As a Platform Engineering Architect you will focus on operationalizing, securing, and maturing artificial intelligence capabilities by building and maintaining the AI "path-to-prod" and a scalable AI run stack—the AI “plumbing.” Your work centers on providing a unified interface for AI model access, integrating foundational and reasoning models, AI agents, and generative AI. Key responsibilities include contributing to the K8s-based AI access platform, managing deployment of core AI services, integrating frontier models (e.g., Claude, GPT) and local inference engines (e.g., vLLM) along with designing MLOps pipelines. The role also requires providing expert recommendations for enterprise AI adoption, specifically in agentic orchestration and spec-driven development.
Heavy emphasis is placed on the GitLab ecosystem and GitOps workflows:
We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.