Software Engineer, Infrastructure & Platform

Jobgether; United States; Remote; USD 110,000 - 160,000; Full time

Benefits offered by this job

Competitive salary

Bonus

Fully remote

Health benefits

PTO

401(k) plan

Professional development

Impactful work

Job summary

Jobgether seeks a Software Engineer, Infrastructure & Platform, to own the backend of large-scale AI evaluation systems. You will design secure, reproducible environments where models can run code and interact with tools.

The role blends cloud infrastructure, distributed systems, and AI safety, with remote U.S.-based work. You will build evaluation platforms, APIs, and tooling, ensuring reliability, observability, and security at scale while collaborating with researchers, analysts, and security

Qualifications

• 3–5+ years of professional software engineering experience in backend, infrastructure, or distributed systems.
• Strong Python programming skills and production-quality software experience.
• Experience designing and operating backend services, APIs, or distributed systems.
• Hands-on experience with Docker, Kubernetes, and virtual machines.
• Experience with AWS or GCP and cloud infrastructure concepts.
• Familiarity with Infrastructure as Code (Terraform) and automation tooling.
• Excellent debugging and troubleshooting across multicomponent systems.
• Ability to build reproducible, observable, scalable, and secure platforms.
• Comfort with ambiguity and rapid architectural changes.
• Strong collaboration with researchers, engineers, analysts, and security experts.

Responsibilities

• Design and build sandboxed evaluation environments for safe AI code execution.
• Develop backend services and infrastructure for large-scale AI evaluations.
• Create agent scaffolding and evaluation harnesses for tool-use loops and workflows.
• Provision environments using Docker, Kubernetes, VMs and cloud infrastructure.
• Implement secure networking, credentials, and secrets management.
• Develop APIs and automation to support researchers and engineers.
• Improve reliability with logging, observability, and automated tests.
• Scale platform to run thousands of evaluation tasks with telemetry capture.
• Collaborate with analysts and domain experts to translate concepts into systems.
• Investigate failures across layers to distinguish model issues from environment problems.

Skills

Python programming

Backend engineering

Distributed systems

Debugging

CI/CD

Tools

Docker

Kubernetes

Virtual machines

Terraform

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Infrastructure & Platform based in the United States.

This is a hands-on engineering role focused on building the infrastructure behind advanced AI evaluations and agentic systems. You’ll design secure, reproducible environments where AI models can execute code, use tools, and complete complex multi-step tasks. The role sits at the intersection of backend engineering, cloud infrastructure, distributed systems, and AI safety. You’ll build scalable evaluation platforms, orchestration systems, APIs, and tooling used by researchers, engineers, and security specialists. A key part of the role is ensuring evaluations are reliable, observable, secure, and reproducible at significant scale. You’ll work alongside analysts, red teamers, and domain experts to turn complex research concepts into robust technical systems. This is a fully remote U.S.-based opportunity suited to an engineer who enjoys ambiguity, deep debugging, and technically challenging problems.

Accountabilities

• Design and build sandboxed evaluation environments that allow AI models to safely execute code, interact with tools and services, and perform complex tasks.
• Develop backend services and infrastructure that support large-scale, repeatable AI and agentic evaluations.
• Build agent scaffolding and evaluation harnesses covering tool-use loops, context management, retries, state management, token budgets, and multi-agent or subagent workflows.
• Provision and orchestrate isolated environments using technologies such as Docker, Kubernetes, virtual machines, and cloud infrastructure.
• Design secure approaches to networking, permissions, credentials, secrets management, and resource isolation for model-driven environments.
• Develop APIs, internal tools, and automation that enable researchers, engineers, and subject-matter experts to efficiently create and execute evaluations.
• Improve evaluation reliability and reproducibility through logging, observability, snapshotting, debugging capabilities, and automated testing.
• Build infrastructure capable of running thousands of evaluation tasks reliably while capturing the artifacts and telemetry required to analyze model behavior.
• Partner with analysts, red teamers, and technical experts to translate sophisticated evaluation concepts into dependable engineering systems.
• Investigate failures across application, infrastructure, networking, and evaluation layers, distinguishing model limitations from problems with the underlying environment or harness.
• Continuously improve platform scalability, security, resilience, and developer experience as evaluation requirements evolve.

Requirements

• 3–5+ years of professional software engineering experience, particularly in backend, infrastructure, platform, SRE, or distributed systems engineering.
• Strong programming skills in Python and experience developing production-quality software.
• Proven experience designing and operating backend services, APIs, or distributed systems.
• Hands‑on experience with Docker, Kubernetes, virtual machines, or comparable container and orchestration technologies.
• Experience working with AWS, GCP, or similar cloud infrastructure platforms.
• Strong understanding of Linux systems, networking, authentication, permissions, and infrastructure security.
• Experience with Infrastructure as Code and automation tools such as Terraform.
• Excellent debugging and troubleshooting abilities across application, infrastructure, and networking layers, including complex agentic workflows.
• Ability to build systems that are reproducible, observable, scalable, reliable, and secure.
• Comfort working through ambiguous technical challenges where requirements and architecture may change rapidly.
• Strong collaboration and communication skills, with the ability to work effectively with researchers, engineers, analysts, and technical specialists.
• Genuine interest in AI systems, agentic workflows, AI security, or model evaluations; previous professional AI experience is beneficial but not mandatory.
• Experience with developer platforms, CI/CD systems, test infrastructure, sandboxes, or ephemeralc compute environments is a plus.
• Familiarity with LLM APIs, agent frameworks, tool‑calling systems, or AI evaluation infrastructure is advantageous.
• Experience designing secure execution environments for untrusted or semi‑trusted code is highly desirable.
• Background in SRE, platform engineering, cloud infrastructure, cybersecurity, or developer tooling is a strong plus.
• Knowledge of distributed task execution, queues, workflow orchestration, or large-scale automated testing is beneficial.
• Familiarity with AI safety, adversarial testing, model evaluations, autonomous agents, or agentic AI concepts—including Model Context Protocol, agent benchmarks, and AI‑agent security risks is advantageous.
• Candidates must be based in the United States and able to meet applicable work authorization requirements.

Benefits

• Competitive salary: $110,000–$160,000 annually, depending on experience and location.
• Performance bonus: Annual performance-based bonus opportunity.
• Fully remote: Work remotely from anywhere in the United States.
• Health coverage: Comprehensive health, dental, and vision benefits.
• Paid time off: Generous PTO and paid holiday schedule.
• Retirement: 401(k) plan.
• Professional development: Support for conferences, continuing education, and leadership training.
• Impactful work: Build infrastructure supporting advanced AI evaluation, safety, security, and research initiatives.

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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