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AI Infrastructure Engineer - Agent Sandbox Platform As a Software Engineer on the AI Infrastructure team, you'll help build and evolve our agent sandboxing platform — the secure, high-performance code execution layer powering our agentic workflows, deployed across both internal and customer-managed environments. This is a role for someone who cares as much about the experience of the engineers and researchers using this system as they do about the kernel internals underneath it. You'll combine deep systems expertise (isolation, virtualization, performance) with an obsession for developer experience: clean APIs, clear error messages, good docs, and a client library that feels well-crafted. You'll partner closely with internal teams to understand how they use the platform, debug their issues, and shape a roadmap that balances immediate needs with long-term architecture. You will: Design and build the sandboxing platform, client library, and API surface for secure code execution across containerized and virtualized environments Ensure strong isolation, security, and reproducibility of execution across user sessions and workloads Optimize for cold-start latency, memory footprint, and resource utilization at scale Drive down error rates through systematic debugging, monitoring, and proactive fixes Partner closely with internal teams using the platform to understand their needs, debug issues, and build tooling that serves their use cases Respond to incidents and production issues with urgency, conducting root cause analysis and implementing preventive fixes Help develop and maintain a product roadmap for sandboxing, balancing immediate needs against long-term architectural investment Lead architecture reviews and own projects end-to-end, from design through deployment, in fast-paced cross-functional settings Ideally you'd have: 4+ years of experience building high-performance systems software, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs Deep understanding of Linux internals: process isolation, memory management, cgroups, namespaces, etc. Experience with containerization and virtualization technologies (e.g., Docker, Firecracker, gVisor, QEMU, Kata Containers) Proficiency in a systems programming language such as Go, Rust, or C/C++ A track record of obsessing over developer experience — API design, error propagation, documentation, and the small details that make a library feel well-crafted Comfort working across infrastructure layers, from kernel modules to orchestration frameworks (e.g., Kubernetes) Strong debugging skills and the ability to navigate performance/security tradeoffs in production systems Comfort with ambiguity, and the ability to context-switch between reactive incident work and proactive product development Nice to haves: Experience as a founder or early engineer at an infrastructure-focused startup, owning a product end-to-end Familiarity with LLM agents and agent frameworks (e.g., OpenHands, Agent2Agent, MCP) Experience running secure workloads in multi-tenant or untrusted environments (e.g., FaaS, CI sandboxes, remote notebooks) Exposure to snapshotting and restore techniques (e.g., CRIU, VM snapshots, overlayfs) Open-source contributions to systems or developer-tools projects History of on-call/incident response for production systems Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $180,000 — $225,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.