Senior Site Reliability Engineer (In-Office Required)

Posted 11 Days Ago
Be an Early Applicant
New York City, NY, USA
In-Office
156K-262K Annually
Senior level
Artificial Intelligence • Information Technology • Consulting
The Role
Own and operate production infrastructure: manage Kubernetes across regions, maintain IaC and GitOps CI/CD workflows, optimize real-time data pipelines, build observability and alerting, debug incidents, and lead cloud cost and capacity planning for a small engineering team.
Summary Generated by Built In

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

About Tavily 

We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed. 

We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world. 

The Role: Senior Site Reliability Engineer 
  • Managing Kubernetes clusters across multiple environments and regions 
  • Owning infrastructure as code for all resources 
  • Maintaining and improving CI/CD pipelines and GitOps-based deployments 
  • Maintaining and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors 
  • Building out monitoring, alerting, and observability 
  • Debugging production issues across services 
  • Managing cloud costs and capacity planning 
  • Working closely with a small engineering team — you'd own infra, not a slice of it 

What we're looking for 

  • 5-8 years in a DevOps or SRE role, working in production environments 
  • Proven experience designing and operating large-scale, distributed systems, with a solid understanding of API design, reliability, and performance at scale 
  • Strong Kubernetes experience in a managed cloud environment 
  • Proficiency with infrastructure as code (Terraform or similar) 
  • Experience with GitOps-based deployment workflows 
  • Built or maintained observability stacks (logging, metrics, alerting) 
  • Experience handling production incidents calmly and methodically 

Nice to have: 

  • Multi-region deployments 
  • Search infrastructure 
  • Data pipeline experience (streaming, warehousing) 
  • Proxy/networking infrastructure at scale 

Why Tavily? 

  • Full ownership — small team, you own the entire infrastructure, not a slice of it 
  • Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests 
  • AI-native company — your infra directly powers AI agents used by leading companies in the space. 

Key employee benefits in the US: 

  • Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 
  • 401(k) plan: Up to 4% company match with immediate vesting. 
  • Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. 
  • Remote work reimbursement: Up to $85/month for mobile and internet. 
  • Disability & life insurance: Company-paid short-term, long-term and life insurance coverage. 

 

Pay Transparency

We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.

Base Compensation Range
$156,000$262,000 USD

Benefits & Perks:

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International environment and talented teams

What's it like to work at Nebius:

Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI 

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. 

If you need accommodations during the application process, please let us know.

Skills Required

  • 5-8 years in a DevOps or SRE role, working in production environments
  • Proven experience designing and operating large-scale, distributed systems with reliability and performance focus
  • Strong Kubernetes experience in a managed cloud environment
  • Proficiency with infrastructure as code (Terraform or similar)
  • Experience with GitOps-based deployment workflows
  • Built or maintained observability stacks (logging, metrics, alerting)
  • Experience handling production incidents calmly and methodically
  • Multi-region deployments
  • Search infrastructure
  • Data pipeline experience (streaming, warehousing)
  • Proxy/networking infrastructure at scale
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The Company
HQ: Amsterdam
473 Employees

What We Do

Cloud platform specifically designed to train AI models

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