Member of Technical Staff - Reliability Engineering
Site Reliability Engineer · Senior · Full Time
Opens Modal's application page
Role
What you'll do.
Modal is seeking a systems-focused Reliability Engineer to be the first dedicated reliability hire, responsible for defining and implementing critical infrastructure reliability strategies for their AI cloud platform. The ideal candidate will be a deep systems thinker with extensive production experience, capable of improving system resilience, designing operational processes, and driving reliability culture across the engineering organization.
Responsibilities
- Reliability Architecture: Identify and implement architectural improvements to enhance system reliability, performance, and availability of Modal's cloud infrastructure.
- Operational Process Design: Design and implement critical operational processes including deployments, upgrades, rollbacks, and comprehensive postmortem reviews.
- Monitoring and Observability: Build robust monitoring systems to ensure high-quality service delivery and proactively identify potential system issues.
- Production Incident Management: Participate in on-call rotations, respond to production incidents, and debug complex issues across all service levels and stack components.
- Reliability Culture Development: Foster a strong culture of reliability and system resilience across Modal's engineering organization.
Qualifications
What we look for.
Technical
Cloud Infrastructure
Deep expertise in cloud technologies, with strong preference for AWS and hyperscaler cloud platforms
Kubernetes Management
Experience scaling Kubernetes clusters to thousands of nodes and managing complex container orchestration environments
Systems Design
Advanced understanding of systems safety research, control theory, and large-scale distributed system architectures
Education
Computer Science or Engineering
Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical field preferred
Experience
Production Engineering
5+ years of experience writing high-quality production code in complex cloud environments
On-Call Experience
Minimum 2 years of on-call experience managing critical production services
Skills
Required
Cloud Infrastructure
Expertise in cloud platforms, particularly AWS, with strong understanding of infrastructure management
Systems Programming
Advanced systems programming skills with ability to write high-performance, reliable production code
Incident Response
Proven ability to diagnose and resolve complex production issues across multiple system layers
Preferred
Systems Safety Research
Nice to haveBackground or experience with STAMP (Systems-Theoretic Accident Model and Processes) and control theory
Capacity Planning
Nice to haveExperience with auto-scaling, fleet management, and large-scale infrastructure capacity planning
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 150,000 – 350,000
Equity·Stock options
Benefits
Equity Compensation
Stock options in a high-growth AI infrastructure startup valued at $1.1B
Career Growth
Opportunity to be the first reliability-focused hire and shape the company's reliability practices
Innovative Work Environment
Join a team of open-source creators, academic researchers, and experienced engineering leaders
Process
Interview steps.
- 01
Initial Screening
Technical resume review and initial recruiter phone screen
- 02
Technical Interview
In-depth technical discussion focusing on systems reliability, cloud infrastructure, and problem-solving skills
- 03
Systems Design Challenge
Architectural design exercise demonstrating candidate's approach to reliability and scalability
- 04
On-Site/Virtual Interviews
Multiple interviews with engineering leadership and potential team members
- 05
Final Interview
Meeting with senior leadership to discuss role alignment and cultural fit
Full posting
Original listing.
About Us:
Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.
We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. Our investors include Lux Capital, Redpoint Ventures, Amplify Partners, and Elad Gil.
Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:
At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform and customer base.
This role is for people who are deep systems thinkers and love stacking nines. You would be the first reliability-focused hire at the company with the opportunity to define the company’s reliability systems and practices, and be a critical partner for our development teams.
Identify architectural changes to improve reliability, performance and availability.
Foster a culture of reliability across Modal’s engineering organization.
Design and implement key operational processes such as deployments, upgrades, rollbacks, and postmortem review.
Join a core engineering team and participate in on-call rotation, responding to production incidents.
Build monitoring systems that ensure the highest quality service for our customers.
Debug production issues across all services and levels of the stack.
Requirements:
5+ years of experience writing high-quality production code.
2+ years of on-call experience for critical production services.
Strong cloud skills, and deep familiarity with at least one hyperscaler cloud (AWS preferred).
Familiarity with auto scaling, fleet management, and capacity planning at scale.
Experience owning and scaling Kubernetes clusters to thousands of nodes a plus.
Experience with systems safety research (e.g. STAMP) and control theory a plus.
Ability to work in-person in our NYC, SF or Stockholm offices.
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