below marketmost similar roles pay hereabove market
This role pays more than
58%
of similar roles. Most pay
$151,000–$216,031
— the blue band above.
At the midpoint, this role pays about
$190k
versus about
$184k
for comparable roles.
Based on 240 similar postings.
Employer
About Arm Holdings
Arm Holdings plc is a leading British semiconductor and software design firm, established in 1990 and recognized for developing energy-efficient processor architectures that power nearly all smartphones and a vast range of IoT and computing devices.
Arm Holdings currently has
113 open roles
on FindRole.
Listed pay typically runs
$208,450–$282,050
across 112 roles with salary data.
The Senior AI Platform Engineer joins the team building a central AI control plane to support safe, scalable, and efficient AI use across engineering teams. This hands-on role involves owning runtime platforms to ensure AI services are reliable, secure, and observable. You will build and operate infrastructure for MCP server infrastructure, model gateway services, and control-plane components while designing patterns for isolation, scalability, and cost-aware operation. Key responsibilities include automating provisioning via infrastructure-as-code, implementing service-level objectives, and managing incident response. You will utilize Kubernetes, containers, cloud platforms, Terraform, Go, and Python. The role requires expertise in AI concepts like RAG systems and LLM observability, alongside security fundamentals including identity, secrets management, network segmentation, and audit logging to provide paved paths for secure AI usage.
Build and operate production infrastructure for centrally hosted AI platform services and model gateways.
Design runtime patterns for workload isolation, scalability, capacity management, and cost-aware operations.
Automate provisioning, configuration, and lifecycle management using infrastructure-as-code and GitOps patterns.
Define and implement service-level indicators, alerting, dashboards, and support workflows.
Manage incident response, post-incident reviews, and vendor outage handling for AI services.
Build telemetry to monitor platform health, usage, performance, cost, and operational risk.
Implement secure runtime patterns including secrets management, identity integration, and network controls.
Participate in a paid on-call rota for high-impact incident response.
What we're looking for
Familiarity with AI platform concepts such as model routing, MCP servers, agentic workflows, RAG systems, or LLM observability.
Strong experience deploying and operating production infrastructure in Linux environments using Kubernetes, containers, cloud platforms, infrastructure-as-code, and CI/CD/GitOps tooling.
Strong automation and scripting skills using Terraform, Go, Python, or similar languages.
Experience with incident management, problem management, demand forecasting, and production readiness practices.
Good understanding of security fundamentals including identity, secrets, access control, network segmentation, vulnerability management, and audit logging.
Experience operating internal developer platforms, AI platforms, model gateways, or other shared engineering platforms (preferred).
Experience with service mesh, policy-as-code, workload identity, sandboxing, or multi-tenant platform designs (preferred).
Experience with regulated or security-sensitive engineering environments (preferred).
AWS
Kubernetes
Docker
Terraform
Python
CloudFormation
CI/CD
MLOps
Amazon Bedrock
SageMaker
Platform One
RMF
DevSecOps
Infrastructure as Code
Iron Bank
Big Bang
ML Infrastructure
Python
C++
Go
Kubernetes
Distributed Systems
Model Serving
C
Java
Rust
Celery
Sidekiq
Temporal
Container Runtimes
EDA Toolchains
SLA Enforcement
Observability