Software Engineer – Infrastructure & Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and construct sandboxed evaluation environments that enable AI models to execute code securely, utilize tools, engage with services, and perform intricate tasks.

• Develop backend services and infrastructure that facilitate large-scale, repeatable evaluations of AI and agentic systems.

• Create agent scaffolding and evaluation harnesses, incorporating tool-use loops, context management, retries, state management, token budgets, and workflows involving multiple agents or subagents.

• Build systems for provisioning and orchestrating isolated environments utilizing Docker, Kubernetes, virtual machines, and cloud infrastructure.

• Devise secure strategies for networking, permissions, secrets, credentials, and resource isolation within model-driven environments.

• Create APIs, internal tools, and automation that empower researchers, engineers, and subject-matter experts to conduct evaluations effectively.

• Enhance evaluation reliability and reproducibility through logging, observability, snapshotting, debugging tools, and automated testing.

• Develop systems capable of executing thousands of evaluation tasks consistently while capturing artifacts and telemetry necessary for understanding model behavior.

• Collaborate with analysts, red team members, and domain experts to convert complex evaluation concepts into robust technical frameworks.

• Examine failures throughout the evaluation stack to differentiate between model limitations and failures in infrastructure, harnesses, or environments.

⛳️ Requirements

• 3–5+ years of professional software engineering experience, especially in backend development, infrastructure, platform, SRE, or distributed systems engineering.

• Proficient programming skills in Python and experience in developing production-quality software.

• Experience in designing and managing backend services, APIs, or distributed systems.

• Practical experience with Docker, Kubernetes, virtual machines, or other container/orchestration technologies.

• Familiarity with AWS, GCP, or comparable cloud infrastructure.

• Strong comprehension of Linux systems, networking, authentication, permissions, and infrastructure security.

• Experience with infrastructure-as-code or automation tools like Terraform.

• Excellent debugging skills across application, infrastructure, and networking layers, particularly in agentic loops.

• Capability to construct systems that are reproducible, observable, scalable, and secure.

• Comfort in addressing ambiguous technical challenges where architecture and requirements may rapidly change.

• Interest in AI systems, agentic workflows, AI security, or model evaluations; previous professional AI experience is advantageous but not mandatory.

🏝️ Benefits

• Performance-based annual bonus.

• Support for conferences, continuing education, or leadership development.

• Fully remote work environment.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and holiday schedule.

• 401(k) plan.