Infrastructure & Platform Engineer
Engineers in this role design, build, and operate the infrastructure systems that power AI model training, inference, and data pipelines at scale. They work across Kubernetes clusters, cloud platforms (AWS, Azure, GCP), GPU compute, networking, and observability tooling—translating the operational needs of researchers and product teams into reliable, performant platform abstractions. What distinguishes this work is its focus on the full lifecycle of AI infrastructure: from provisioning and scaling compute for large training runs, to optimizing data movement and storage efficiency, to diagnosing performance bottlenecks across distributed systems under real workload pressure. These engineers typically sit within dedicated infrastructure or platform teams that directly enable research velocity and production reliability, partnering closely with ML researchers and other product engineers to remove friction from experiment-to-production workflows.
Measured across 532 of 536 open postings.
This role is advertised at 4 levels, so a single figure for the role would describe none of them. Experience and pay are the midpoints for each level on its own.
| Level | Share | Median years | Median pay |
|---|---|---|---|
| Entry | 2%(11) | — | — |
| Mid | 36%(189) | 4 | $308k |
| Senior | 27%(142) | 5 | $300k |
| Staff / Principal | 34%(183) | 8 | $273k |
A dash means too few postings stated it to report a midpoint. Most companies do not publish a salary band, so pay is indicative rather than a market rate. 1 level with fewer than 10 open postings is not shown.
“Build AI-powered internal tools that leverage LLMs and intelligent workflows to assist support agents”
“Write production code using AI-assisted development tools (Claude Code, Cursor)”
“Use AI-assisted development tools with judgment: accelerate exploration and implementation while independently verifying correctness, security, and maintainability.”
“set direction, influence engineering culture, and create learnings that may inform both internal engineering productivity and n8n's external product”
Requirements are a share of every open posting, so a role missing from this list is one where almost nobody asks. Work mode is different: many postings never say, so that figure counts only the ones that do. A posting stops being advertised when it is filled, cancelled or reorganised, so read the last figure as how long these stay on the market, not as time to hire.
Share of new postings expecting AI in the person's own work, by the week they appeared. Measured on the same 124 companies throughout, every one of them tracked since 18 May, so the line is not moved by us adding companies.
Line is a four-week average; dots are individual weeks, 21 postings each on average. Weekly values span 50 points across this window, so read the line, not the gap between two dots.
Skills
What companies are looking for in this role.
Distributed systems architecture
Cloud infrastructure operations
Infrastructure automation and IaC
Monitoring and observability
Backend and API engineering
Systems performance optimization
Incident response and reliability
Developer platform engineering
CI/CD and release automation
Data pipeline engineering
Network engineering and operations
Database and storage engineering
Technical program management
Security engineering
Cloud and infrastructure security
AI and GPU infrastructure operations
Mentoring and code review
Technology
The tools and technologies that define this role.
Open Jobs
536 open Infrastructure & Platform Engineer jobs across 87 companies.
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