retries jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, retries appears in 499 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning retries, with demand share up 22.6% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
499
Demand vs prior month
up 22.6% vs the prior 4 weeks
Top role · 37.1% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about retries

+Is retries in demand in 2026?

Yes. retries appears in 499 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning retries (37.1% of all postings mentioning retries).

+What jobs require retries?

According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning retries are Core Infrastructure Engineer (18.6% of that role’s postings mention retries), Frontier Agents Engineer (18.2% of that role’s postings mention retries), Agent Engineer (9.5% of that role’s postings mention retries).

+What skills are commonly paired with retries?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), retries most often appears alongside idempotency, observability, Python, TypeScript, Distributed systems.

+Where is retries most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring retries are San Francisco, Bengaluru, London, New York City, Seoul, according to the Skillenai jobs index.

+How can I keep up with new retries content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning retries alongside the jobs index. You can subscribe to a daily email digest of new retries content from your Skillenai account.

+Which skills come before and after retries?

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 retries — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around retries

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before retries

Before retriespredictive analytics → retries: 1 observed employer moves with this skill pairpython → retries: 1 observed employer moves with this skill pairmachine learning algorithms → retries: 1 observed employer moves with this skill pairdata streaming pipelines → retries: 1 observed employer moves with this skill pairNoSQL databases → retries: 1 observed employer moves with this skill pairdata storage → retries: 1 observed employer moves with this skill pairdata retrieval → retries: 1 observed employer moves with this skill pairsql → retries: 1 observed employer moves with this skill pairretriespredictive analytics: 1 movespredictiveanalytics1 movespython: 1 movespython1 movesmachine learning algorithms: 1 movesmachine learningalgorithms1 movesdata streaming pipelines: 1 movesdata streamingpipelines1 movesNoSQL databases: 1 movesNoSQL databases1 movesdata storage: 1 movesdata storage1 movesdata retrieval: 1 movesdata retrieval1 movessql: 1 movessql1 moves

Skills after retries

After retriesretries → Third-party APIs: 1 observed employer moves with this skill pairretries → automated testing: 1 observed employer moves with this skill pairretries → CI/CD pipelines: 1 observed employer moves with this skill pairretriesThird-party APIs: 1 movesThird-party APIs1 movesautomated testing: 1 movesautomated testing1 movesCI/CD pipelines: 1 movesCI/CD pipelines1 moves
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.

Observed connections and move counts
ConnectionMoves
Before: predictive analytics1
Before: python1
Before: machine learning algorithms1
Before: data streaming pipelines1
Before: NoSQL databases1
Before: data storage1
Before: data retrieval1
Before: sql1
After: Third-party APIs1
After: automated testing1
After: CI/CD pipelines1

Roles most likely to require retries

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Core Infrastructure Engineer818.6%
Frontier Agents Engineer418.2%
Agent Engineer29.5%
iOS Software Engineer118.4%
Integrations Engineer27.1%
Integration Developer14.8%
Business Systems Engineer24.5%
Computer Scientist14.0%
Python Engineer23.8%
Professional Services Engineer23.6%

Roles with the most retries postings

RolePostings mentioning skillShare of skill postings
Software Engineer18537.1%
Backend Engineer438.6%
Product Manager234.6%
Platform Engineer112.2%
iOS Software Engineer112.2%
Forward Deployed Engineer91.8%
Technical Lead91.8%
Core Infrastructure Engineer81.6%
AI Engineer71.4%
Engineering Manager71.4%

Top companies posting jobs requiring retries

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring retries
CompanyPostings · 90 days
Bjakcareer40
CLERA10
Oracle10
Fundraise Up8
Together AI7
Bjak6
Twilio5
OpenFX5
Commvault5
NVIDIA5

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 retries

NamePostingsShare
San Francisco357.0%
Bengaluru173.4%
London173.4%
New York City163.2%
Seoul112.2%
Singapore102.0%
Berlin81.6%
Copenhagen81.6%
Palo Alto81.6%

Skills commonly paired with retries

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. 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 retries by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s retries postings by all retries 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: 0.2% to 0.2%. 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 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (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
9b7a8e1c8fe5a933
data_as_of
2026-09-30
window_days
90
Hiring engineers who use retries?

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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Compiled by Jared Rand · Data sourced from the Skillenai labor market index