Junior AI Platform Engineer

About the Role

• Early-career role built for growth.
• Join a platform engineering team that builds and operates enterprise AI platforms and services.
• Work alongside senior engineers for technical direction, mentorship, and hands-on guidance.
• Gain practical experience building, deploying, operating, and troubleshooting scalable AI infrastructure and services.
• Progressively take greater ownership of platform engineering responsibilities as skills develop.

Key Responsibilities

• Deploy, operate, and administer enterprise AI platforms and services using Docker, Kubernetes, and Helm.
• Develop, enhance, and maintain software and infrastructure to improve platform operations, monitoring, and reliability.
• Troubleshoot infrastructure, application, and user issues.
• Analyze AI platform reliability and performance: conduct benchmarks, identify bottlenecks, and implement improvements.
• Participate in design discussions, code reviews, documentation, testing, and other team engineering activities.
• Assist in identifying and evaluating emerging AI technologies and assessing their suitability for lab use.
• Learn and apply platform engineering, DevOps, MLOps, and administration automation practices.
• Share knowledge and contribute to a collaborative environment focused on continuous learning and improvement.
• Engage in mentorship and technical guidance from senior team members while progressively taking ownership of platform engineering responsibilities.

Requirements & Tech Stack

• Linux environments and basic system administration concepts.
• Container technologies (such as Docker) and container orchestration technologies (such as Kubernetes).
• CI/CD and other DevOps concepts.
• Python or a similar programming language.
• Understanding of AI/ML concepts and an interest in foundation models and Large Language Models (LLMs).
• Familiarity with LLM application patterns including RAG, tool/function-calling, MCP, and agentic workflows.
• Familiarity with agentic harnesses such as Codex, Claude Code, or OpenCode.
• Ability to investigate and troubleshoot technical problems using documentation, research, logs, and guidance from more experienced engineers.
• Comfortable learning and adopting new technologies.
• Ability to obtain an Interim Secret level security clearance by your start date and ultimately obtain a Secret level clearance.
• U.S. citizenship is required.
• Subject to a government security clearance investigation.

Qualifications

• Bachelor's or Master's degree in Computer Science or a related field.

Going Above and Beyond

• Demonstrated experience managing applications deployed to Kubernetes, especially using Helm.
• Demonstrated experience developing and maintaining CI/CD pipelines and other DevOps artifacts.
• Experience with at least one cloud computing platform (AWS, Azure, GCP).
• Experience securing cloud-native applications.
• Proficiency with LLM application patterns.
• Proficiency with agentic harnesses.
• Hands-on experience with MLOps and Agile processes.

Special Working Conditions

• Occasional weekend and other after-hours work may be required to handle and/or complete critical work.