Skill
Autoscaling
Cloud Computing and DevOps
Autoscaling is a cloud computing capability that automatically adjusts the number of compute resources—such as servers or containers—allocated to an application based on real-time demand. DevOps engineers and cloud architects use autoscaling in platforms like AWS, Azure, and Kubernetes to maintain performance during traffic spikes while minimizing costs during periods of low usage.
Autoscaling in the job market
Last checked September 13, 2026
- Open roles
- 6
- Employers
- 4
- Median pay
- —
- Disclose pay
- —
on Career App right now
hiring for it
not enough disclosed
of these roles
Open roles requiring Autoscaling (6)
Principal Engineer (AWS & Java)
LSEG
This Principal Engineer role leads the technical implementation of a major risk screening platform at a global financial infrastructure company, focusing on AWS cloud systems and Java performance at scale. The position suits deeply experienced engineers who excel at solving complex distributed systems problems and mentoring senior technical teams while maintaining hands-on involvement in critical implementations.
Listed on LSEG’s careers site · Apply there ↗
Member of Technical Staff - Research, Inference
Modal
New York, NY · $150,000 – $350,000
Modal is hiring a researcher to lead inference optimizations for their LLM serving platform, focusing on techniques like speculative decoding and quantization that reduce cost and latency. This role suits someone with a background shipping inference systems or research who can independently drive projects from conception through deployment.
Listed on Modal’s careers site · Apply there ↗
Staff + Senior Software Engineer, Inference Infrastructure
Menlo Ventures Portfolio
Full-time · New York, NY · $320,000 – $485,000
This role leads the inference infrastructure systems that deliver Claude to millions of users, focusing on distributed systems architecture, request routing, load balancing, and fleet orchestration across diverse AI hardware. It suits experienced distributed systems engineers who want to work on large-scale production challenges where performance directly impacts both business growth and AI research capability.
Listed on Menlo Ventures Portfolio’s careers site · Apply there ↗
Senior Software Engineer, Compute (Temporal Cloud)
Temporal
Full-time · United States - Remote Opportunity · $176,000 – $237,600
This role involves building the managed compute platform that powers Temporal Cloud, designing autoscaling systems and execution primitives that keep worker fleets safe, observable, and elastic across multiple cloud providers. It suits someone with deep experience in distributed systems and multi-tenant platforms who enjoys owning infrastructure on the critical path and collaborating across teams to ship cohesive platform changes.
Listed on Temporal’s careers site · Apply there ↗
Staff + Sr. Software Engineer, Cloud Inference
Menlo Ventures Portfolio
Full-time · San Francisco, CA · $320,000 – $485,000
This role leads the infrastructure that delivers Claude AI across multiple cloud platforms, balancing performance and cost at massive scale. It's ideal for backend engineers who excel at cross-platform system design and can navigate the complexity of serving billions of inference requests across AWS, GCP, Azure, and beyond.
Listed on Menlo Ventures Portfolio’s careers site · Apply there ↗
Staff Software Engineer, Compute (Temporal Cloud)
Temporal
Full-time · United States - Remote Opportunity · $212,000 – $286,000
This Staff Software Engineer role focuses on building the managed compute infrastructure that powers Temporal Cloud, designing autoscaling systems and platform primitives for distributed worker execution. It suits experienced platform engineers who have shipped infrastructure systems used by other teams and want to work on the challenging problems of making cloud compute safe, observable, and elastic across multiple execution environments.
Listed on Temporal’s careers site · Apply there ↗
Roles that use Autoscaling
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