Backend Engineer
Backend Engineers at AI companies build and operate the server-side systems that AI products and infrastructure run on—distributed services, REST APIs, data pipelines, and the databases behind them. The day-to-day is classical backend work: designing services for reliability and scale, optimizing query performance, instrumenting observability, owning on-call and SLOs, and partnering with product and frontend teams to ship features end-to-end. AI-specific surfaces—high-throughput inference serving paths, telemetry pipelines for GPU-dense infrastructure, agent runtime systems—appear in some of these jobs, particularly at infrastructure and platform companies, but the canonical role is recognizable as backend engineering across any high-growth software business. Backend Engineers typically sit within product, platform, or core services teams, often as the foundational layer that both product engineers and ML engineers build on top of.
Measured across 496 of 499 open postings.
This role is advertised at 3 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 |
|---|---|---|---|
| Mid | 30%(150) | 4 | $259k |
| Senior | 37%(182) | 5 | $250k |
| Staff / Principal | 31%(153) | 8 | $295k |
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 Most companies do not publish a salary band, so pay is indicative rather than a market rate. 3 levels with fewer than 10 open postings are not shown.
“Design and build scalable agentic systems, backend services and data-processing workflows that transform complex, unstructured customer data into reliable, structured outputs”
“Experience rationally leveraging AI coding assistants and LLMs (e.g., Claude, Cursor, Gemini) to accelerate development”
“You'll leverage agentic AI tools as part of your daily workflow”
“design, build, and operate the systems that connect models with search at ChatGPT scale”
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, 18 postings each on average. Weekly values span 37 points across this window, so read the line, not the gap between two dots.
Skills
What companies are looking for in this role.
Backend and API engineering
Distributed systems architecture
Systems performance optimization
Data pipeline engineering
Cloud infrastructure operations
Monitoring and observability
Database and storage engineering
Incident response and reliability
Security engineering
Technical program management
Infrastructure automation and IaC
Full-stack product engineering
Developer platform engineering
Agent system architecture and development
Mentoring and code review
Technology
The tools and technologies that define this role.
Open Jobs
499 open Backend Engineer jobs across 100 companies.
Other Engineering roles
General-purpose software engineering roles focused on building and maintaining software systems. Covers generalist SWE positions that don't clearly fall into frontend, backend, fullstack, or other specialized tracks.
Engineers specializing in user-facing interfaces, web applications, and client-side development. Includes UI/UX engineering and web development roles.
Engineers working across the entire application stack, handling both frontend and backend responsibilities.
Engineers building and maintaining internal platforms, cloud infrastructure, compute systems, and developer tooling.
Engineers embedded with customers or deployed on-site to solve domain-specific technical problems. Combines engineering skills with direct client interaction.