About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role: We’re looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy.
What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container & Orchestration Security Secure and harden containerized workloads and orchestration systems (e.g., Kubernetes or similar) Improve workload isolation, scheduling boundaries, and runtime protections Evaluate tradeoffs in multi-tenant execution models Identity & Access Management Design and improve authentication and authorization systems across services Implement strong service-to-service identity and least-privilege access patterns Improve access controls across infrastructure and internal systems Secrets & Key Management Build and maintain systems for securely managing secrets, tokens, and credentials Improve rotation, auditing, and access controls Reduce secret sprawl and integrate secure patterns into developer workflows Cloud & Infrastructure Security Secure cloud environments across providers (AWS, GCP, etc.) with a focus on consistency and portability Improve network boundaries, service segmentation, and access controls Embed security into infrastructure-as-code and deployment systems Engineering Partnership Work closely with product and infrastructure teams to design secure systems from the ground up Review architecture and code for security risks and provide actionable guidance Identify patterns in risks and drive cross-cutting improvements
Requirements: Core Experience Experience securing cloud-native infrastructure and distributed systems in production Background in infrastructure, backend, or security engineering Experience working in multi-tenant or high-scale environments Technical Depth Strong understanding of containerization and orchestration systems (e.g., Kubernetes or similar) Experience designing or securing isolation mechanisms in multi-tenant systems Solid understanding of authentication, authorization, and service identity models Experience with secrets management and secure handling of credentials Strong foundation in networking concepts (segmentation, service communication, access boundaries) Mindset Builder mentality, you design and implement, not just review Pragmatic approach to security in fast-moving environments Comfortable working deeply with engineers and influencing system design Preferred
Qualifications: Experience with sandboxing or runtime isolation technologies (e.g., gVisor, Firecracker, seccomp, or similar) Familiarity with kernel-level or low-level isolation primitives Experience securing Kubernetes or similar orchestration systems in production Background in developer infrastructure, compute platforms, or multi-tenant systems
Modal is a serverless cloud infrastructure platform designed for running artificial intelligence, machine learning, and data processing workloads using code-based configuration. The company provides an environment where developers deploy functions for inference, training, batch processing, and data pipelines without managing servers or manual infrastructure setup. It offers GPU access and CPU resources that automatically scale based on workload demand, supporting applications such as large language model inference, model fine-tuning, and high-throughput computation tasks. Modal includes sandbox environments that execute isolated code for testing, evaluation, and agent-based workflows. The platform also integrates observability features that allow monitoring of logs, execution states, and performance metrics across workloads. It supports multi-cloud GPU scheduling and dynamic resource allocation to optimize compute availability across regions. Modal is used by teams building AI applications that require flexible compute scaling, low-latency execution, and simplified deployment workflows.
Salary
$150,000 - $270,000
Location
New York, NY
Total raised
$111M
Last stage
Growth
Investors
Akshat Bubna
CTO and Co-Founder
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.