9 часов назад
Infrastructure Engineer (AI Security)
180 000 - 290 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Infrastructure Engineer (AI Security) (Kubernetes/AWS): Building and scaling backend services, distributed infrastructure, and cloud architecture for an AI security platform with an accent on reliability, scalability, observability, and secure AI workloads. Focus on designing highly available systems, optimizing performance and costs, and building production infrastructure for machine learning and security teams.
Location: Pittsburgh or remote within the United States; hybrid work arrangement
Salary: $180,000–$290,000 annually, plus performance-based bonus and meaningful equity
Company
is an AI security startup that evaluates frontier AI models and builds real-time threat detection and adversarial red-teaming systems.
What you will do
- Design, build, and maintain highly available backend services and distributed systems for the AI security platform.
- Own cloud infrastructure across Kubernetes, AWS, networking, storage, and compute.
- Build scalable APIs, internal platform services, and infrastructure tooling.
- Improve observability through logging, metrics, tracing, dashboards, and automated alerting.
- Optimize performance, latency, infrastructure costs, reliability, and security.
- Partner with machine learning, security, and product engineering teams on production AI infrastructure.
Requirements
- 5+ years of experience building backend infrastructure or distributed systems in production.
- Strong programming skills in C/C++, Go, Python, Rust, or Java.
- Experience operating Kubernetes services and modern cloud platforms such as AWS, GCP, or Azure.
- Deep knowledge of networking, distributed systems, containers, service orchestration, and scalable architectures.
- Experience designing APIs, microservices, asynchronous systems, and event-driven architectures.
- Ability to debug complex production issues and improve reliability through automation.
Nice to have
- Experience supporting machine learning or LLM infrastructure.
- Infrastructure-as-code experience and familiarity with Kafka, Redis, PostgreSQL, ClickHouse, or similar systems.
- Experience building internal developer platforms or platform engineering tools.
- Knowledge of cloud security, infrastructure hardening, or zero-trust architectures.
- Experience at a high-growth startup or with AI safety, cybersecurity, or adversarial machine learning.
Culture & Benefits
- Significant ownership over foundational systems and technical direction.
- 401(k) with up to 4% matching.
- 28 days of annual leave, including vacation and holidays.
- Health, dental, and vision coverage.
- Flexible work arrangements and catered lunches at the Pittsburgh office.
- Visa sponsorship is available for exceptional candidates.
Hiring process
- Application review followed by a 15-minute online technical screen.
- Introductory call, technical interview with live coding, and experience and culture interview.
- Reference checks with 3–5 references, followed by an offer.
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