Сильная возможность в сфере AI-инфраструктуры: понятная техническая ответственность и заметный рост компании, хотя роль охватывает несколько разных платформенных направлений.
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Широкий охватАктуальный стекБыстрорастущая сфераСильный импульс ростаРасширенные льготы
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Hirify AI/Оригинал
TL;DR
Backend/Distributed Systems Engineer (AI): Building scalable observability, commercialization, billing, internal infrastructure, and AI agent platforms for production AI inference with an accent on distributed systems, telemetry pipelines, and developer productivity. Focus on designing multi-cloud platforms, improving reliability and deployment safety, and defining testing and operational standards across engineering teams.
Location: Hybrid in San Francisco, New York, or Seattle, United States.
Salary: $165K–$330K annually, plus equity.
Company
Baseten provides an AI inference platform, infrastructure, and developer tooling that help AI companies bring machine-learning models into production.
What you will do
Design and build scalable telemetry ingestion and storage pipelines for metrics, logs, and traces across multi-cloud infrastructure.
Own observability platforms, commercialization and billing systems, partnership integrations, and internal AI agent infrastructure.
Develop internal tooling that improves developer velocity, CI/CD, deployment safety, testing, alerting, incident response, and production debugging.
Drive platform adoption through self-service developer experience, good defaults, clear documentation, and low-friction workflows.
Lead technical design for cross-team projects and make trade-offs between delivery speed, quality, reliability, cost, and maintainability.
Partner with infrastructure, model performance, and product teams while contributing through code review, mentorship, and technical writing.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
5+ years of relevant industry experience focused on scalable backend systems and platforms.
Experience building or operating observability systems covering logging, metrics, and tracing, or operating internal infrastructure at scale.
Proficiency in Python, Go, Rust, or a similar backend language.
Strong understanding of quality and engineering principles, including both the purpose and implementation of engineering decisions.
Strong systems-level thinking and understanding of interactions between distributed-system components and data flows.
Platform mindset focused on adoption, self-service, internal engineers as customers, and effective defaults.
Excellent written and verbal communication skills.
Culture & Benefits
Meaningful equity and competitive compensation.
For U.S. employees, 100% coverage of medical, dental, and vision insurance for employees and dependents.
Flexible PTO and a company-wide Winter Break from Christmas Eve through New Year’s Day.
Paid parental leave and a fertility and family-building stipend through Carrot.
For U.S. employees, a company-facilitated 401(k).
Exposure to ML startups and opportunities for learning and networking.
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