Skillenai

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

As of 2026-10-21, knowledge graphs appears in 676 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning knowledge graphs, with demand share up 6.3% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-21

Postings · last 90 days
676
Demand vs prior month
up 6.3% vs the prior 4 weeks
Top role · 10.7% of skill postings
Software Engineer
Top hiring metro
New York City

Which roles want knowledge graphs?

Upload your resume and Skillenai will show which roles your knowledge graphs experience fits, which skills you already cover, and what is missing.

See which roles your knowledge graphs experience fits →No account needed.

Frequently asked questions about knowledge graphs

+Is knowledge graphs in demand in 2026?

Yes. knowledge graphs appears in 676 job postings indexed by Skillenai over the 90 days ending 2026-10-21. Software Engineer accounts for the most postings mentioning knowledge graphs (10.7% of all postings mentioning knowledge graphs).

+What jobs require knowledge graphs?

According to the Skillenai jobs index over the 90 days ending 2026-10-21, among roles with at least 20 postings, the highest shares mentioning knowledge graphs are Data Modeler (21.9% of that role’s postings mention knowledge graphs), AI Lead (9.1% of that role’s postings mention knowledge graphs), Applied AI Scientist (8.3% of that role’s postings mention knowledge graphs).

+What skills are commonly paired with knowledge graphs?

Across job postings indexed by Skillenai (90 days ending 2026-10-21), knowledge graphs most often appears alongside Python, RAG, machine learning, LLMs, vector databases.

+Where is knowledge graphs most in demand?

As of 2026-10-21, the metro areas posting the most jobs requiring knowledge graphs are New York City, Hyderabad, London, San Francisco, San Jose, according to the Skillenai jobs index.

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

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

+Which skills come before and after knowledge graphs?

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 knowledge graphs — last 90 days

Salary distribution

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

Career paths around knowledge graphs

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before knowledge graphs

Before knowledge graphssql → knowledge graphs: 6 observed employer moves with this skill pairpython → knowledge graphs: 4 observed employer moves with this skill pairJavaScript → knowledge graphs: 3 observed employer moves with this skill pairtesting → knowledge graphs: 2 observed employer moves with this skill pairPower BI → knowledge graphs: 2 observed employer moves with this skill pairreact.js → knowledge graphs: 2 observed employer moves with this skill pairTableau → knowledge graphs: 2 observed employer moves with this skill pairJava → knowledge graphs: 2 observed employer moves with this skill pairknowledgegraphssql: 6 movessql6 movespython: 4 movespython4 movesJavaScript: 3 movesJavaScript3 movestesting: 2 movestesting2 movesPower BI: 2 movesPower BI2 movesreact.js: 2 movesreact.js2 movesTableau: 2 movesTableau2 movesJava: 2 movesJava2 moves

Skills after knowledge graphs

After knowledge graphsknowledge graphs → python: 3 observed employer moves with this skill pairknowledge graphs → feature engineering: 2 observed employer moves with this skill pairknowledge graphs → TypeScript: 2 observed employer moves with this skill pairknowledge graphs → ci/cd: 1 observed employer moves with this skill pairknowledge graphs → osmnx: 1 observed employer moves with this skill pairknowledge graphs → clustering algorithms: 1 observed employer moves with this skill pairknowledge graphs → ROC: 1 observed employer moves with this skill pairknowledge graphs → entropy: 1 observed employer moves with this skill pairknowledgegraphspython: 3 movespython3 movesfeature engineering: 2 movesfeatureengineering2 movesTypeScript: 2 movesTypeScript2 movesci/cd: 1 movesci/cd1 movesosmnx: 1 movesosmnx1 movesclustering algorithms: 1 movesclusteringalgorithms1 movesROC: 1 movesROC1 movesentropy: 1 movesentropy1 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: sql6
Before: python4
Before: JavaScript3
Before: testing2
Before: Power BI2
Before: react.js2
Before: Tableau2
Before: Java2
After: python3
After: feature engineering2
After: TypeScript2
After: ci/cd1
After: osmnx1
After: clustering algorithms1
After: ROC1
After: entropy1

Roles most likely to require knowledge graphs

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

RolePostings mentioning skill% of role postings mentioning skill
Data Modeler721.9%
AI Lead29.1%
Applied AI Scientist38.3%
ML Infrastructure Engineer36.5%
Database Architect26.2%
GenAI Engineer25.7%
Agentic AI Engineer35.1%
Data Governance Analyst15.0%
Full Stack AI Engineer24.9%
Data Science Engineer24.8%

Roles with the most knowledge graphs postings

RolePostings mentioning skillShare of skill postings
Software Engineer7210.7%
AI Engineer497.2%
Data Scientist456.7%
Product Manager324.7%
Data Engineer263.8%
Machine Learning Engineer162.4%
ML Engineer152.2%
AI/ML Engineer131.9%
Data Architect131.9%
Forward Deployed Engineer111.6%

Top companies posting jobs requiring knowledge graphs

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

Top companies posting jobs requiring knowledge graphs
CompanyPostings · 90 days
CLERA23
Accenture20
Onebrief14
Elsevier12
Together AI9
Scale AI8
TTEC7
Adobe7
ServiceNow7
Neo4j7

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 knowledge graphs

NamePostingsShare
New York City304.4%
Hyderabad243.6%
London243.6%
San Francisco192.8%
San Jose121.8%
Singapore121.8%
Bengaluru111.6%
Seattle111.6%
San Mateo101.5%

Skills commonly paired with knowledge graphs

Python (297)RAG (142)machine learning (130)LLMs (114)vector databases (110)ontologies (99)AWS (96)embeddings (95)prompt engineering (88)Retrieval-Augmented Generation (RAG) (88)

Explore related pages

How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-21. 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 knowledge graphs by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s knowledge graphs postings by all knowledge graphs 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: 0.3% to 0.3%. 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 2,610 identified employers and covers 72% of earlier and 73% of latest indexed postings. Windows: 2026-06-23 to 2026-09-21 and 2026-07-21 to 2026-10-19 (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
fc4048961fcf1701
data_as_of
2026-10-21
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index