system reliability jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-08, system reliability appears in 278 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning system reliability, with demand share up 0.2% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-08
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Frequently asked questions about system reliability
+Is system reliability in demand in 2026?
Yes. system reliability appears in 278 job postings indexed by Skillenai over the 90 days ending 2026-10-08. Software Engineer accounts for the most postings mentioning system reliability (25.5% of all postings mentioning system reliability).
+What jobs require system reliability?
According to the Skillenai jobs index over the 90 days ending 2026-10-08, among roles with at least 20 postings, the highest shares mentioning system reliability are Machine Learning Manager (15.4% of that role’s postings mention system reliability), Machine Learning Infrastructure Engineer (6.5% of that role’s postings mention system reliability), Software Engineering Technical Leader (4.4% of that role’s postings mention system reliability).
+What skills are commonly paired with system reliability?
Across job postings indexed by Skillenai (90 days ending 2026-10-08), system reliability most often appears alongside Distributed systems, observability, Python, AWS, TypeScript.
+Where is system reliability most in demand?
As of 2026-10-08, the metro areas posting the most jobs requiring system reliability are London, Mountain View, Toronto, San Francisco, New York City, according to the Skillenai jobs index.
+How can I keep up with new system reliability content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning system reliability alongside the jobs index. You can subscribe to a daily email digest of new system reliability content from your Skillenai account.
+Which skills come before and after system reliability?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring system reliability — last 90 days
Career paths around system reliability
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before system reliability
Skills after system reliability
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: automation | 2 |
| Before: python | 2 |
| Before: Grafana | 2 |
| Before: sql | 2 |
| Before: troubleshooting | 2 |
| Before: Azure | 2 |
| Before: GitHub Actions | 2 |
| Before: terraform | 2 |
| After: intelligent automation | 1 |
| After: software and data engineering | 1 |
| After: infrastructure | 1 |
| After: distribution center operations | 1 |
| After: ci/cd | 1 |
| After: ETL | 1 |
| After: optimization | 1 |
| After: predictive analytics | 1 |
Roles most likely to require system reliability
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Machine Learning Manager | 4 | 15.4% |
| Machine Learning Infrastructure Engineer | 2 | 6.5% |
| Software Engineering Technical Leader | 2 | 4.4% |
| Technical Lead Manager | 1 | 3.7% |
| Quality Engineering Manager | 1 | 3.6% |
| Software Engineering Director | 3 | 3.4% |
| Information Technology Specialist | 1 | 3.3% |
| Product Architect | 1 | 3.2% |
| Senior Data Engineer | 1 | 2.8% |
| Developer Advocate | 1 | 2.2% |
Roles with the most system reliability postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 71 | 25.5% |
| Engineering Manager | 40 | 14.4% |
| Product Manager | 13 | 4.7% |
| DevOps Engineer | 12 | 4.3% |
| Backend Software Engineer | 10 | 3.6% |
| Site Reliability Engineer | 8 | 2.9% |
| Backend Engineer | 7 | 2.5% |
| Systems Engineer | 7 | 2.5% |
| Data Engineer | 6 | 2.2% |
| Technical Product Manager | 5 | 1.8% |
Top companies posting jobs requiring system reliability
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Stripe | 19 |
| Waymo | 10 |
| 7 | |
| Cisco | 6 |
| Spotify | 5 |
| 4 | |
| Scout Motors | 4 |
| Unity | 4 |
| BeaconOS | 3 |
| Wayve | 3 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for system reliability
| Name | Postings | Share |
|---|---|---|
| London | 12 | 4.3% |
| Mountain View | 12 | 4.3% |
| Toronto | 11 | 4.0% |
| San Francisco | 10 | 3.6% |
| New York City | 7 | 2.5% |
| Berlin | 4 | 1.4% |
| Charlotte | 4 | 1.4% |
| Tokyo | 4 | 1.4% |
| Austin | 3 | 1.1% |
Skills commonly paired with system reliability
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-08. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning system reliability by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s system reliability postings by all system reliability postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,617 identified employers and covers 70% of earlier and 72% of latest indexed postings. Windows: 2026-06-09 to 2026-09-07 and 2026-07-07 to 2026-10-05 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- b79c85f8f10b7501
- data_as_of
- 2026-10-08
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
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