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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 October 28, 2026

Open roles
7

on Career App

Employers
6

hiring for it

Median pay
—

not enough disclosed

Disclose pay
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of these roles

Open roles requiring Autoscaling (7)

Forward Deployed Engineer

Render

SF or Remote (US/Canada) · $236,000 – $289,000

Render seeks an experienced field engineer to be their first Forward Deployed Engineer, serving as a dedicated technical partner to their largest customers and fastest-growing AI startups. This role combines hands-on architecture and migration work—particularly database expertise—with customer success and product feedback responsibilities while establishing the playbook for the function.

Listed on Render’s careers site · Apply there ↗

Engineering Manager, Inference Infrastructure

Menlo Ventures Portfolio

Full-time · New York, NY · $405,000 – $625,000

Lead the technical strategy and day-to-day operations of the team that manages traffic routing, capacity allocation, and load balancing across Anthropic's Claude inference infrastructure. This role requires deep systems expertise to make architectural decisions about fleet coordination, ship measurable performance improvements, and develop a strong team of infrastructure and distributed-systems engineers.

Listed on Menlo Ventures Portfolio’s careers site · Apply there ↗

Customer Success Manager, Managed Inference

Crusoe

Full-time · San Francisco, CA · $175,000 – $200,000

This role supports enterprise customers deploying AI inference workloads on Crusoe's infrastructure platform, bridging technical and business needs while helping optimize model serving and GPU utilization. It suits someone with cloud platform experience and a solid understanding of AI/ML technologies who enjoys hands-on customer engagement and cross-team coordination.

Listed on Crusoe’s careers site · Apply there ↗

Staff Product Manager, Cloud Namespace & Capacity

Temporal

Full-time · United States - Remote Opportunity · $185,000 – $260,000

This role owns the product experience for Temporal Cloud's namespace offering, from provisioning through operation, working across engineering and operations teams to balance reliability, performance, and cost at scale. It suits experienced product leaders comfortable with infrastructure systems thinking who can translate technical tradeoffs into customer-facing capabilities and policies.

Listed on Temporal’s careers site · Apply there ↗

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 drive inference optimization for their AI infrastructure platform, focusing on techniques like speculative decoding and quantization that reduce cost-per-token and latency for production LLM workloads. This role suits someone with a background in LLM systems who can own research projects end-to-end, collaborate with customers and external labs, and ship work that becomes part of Modal's serving stack.

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 ↗

Employers hiring for Autoscaling

6 in total, most open roles first.

Related skills

Curated neighbors in the taxonomy, whether or not employers ask for them together.

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