Bullhorn Resume Parsing API
★ Only Publicly Available OpenAPI DocumentHR recruitingRecruiting Atsoauth29 EndpointsREST
For Agents
Parse resume files into structured candidate data and create Bullhorn ATS candidates with education, work history, skills, and file attachments.
Use for: I need to parse a candidate resume into Bullhorn, Create a new candidate record from an uploaded CV, Attach a work history entry to an existing Bullhorn candidate, Add primary skills to a candidate I just imported
Not supported: Does not handle job postings, interview scheduling, or payroll — use for resume parsing and candidate creation in Bullhorn only.
Jentic publishes the only available OpenAPI specification for Bullhorn Resume Parsing API, keeping it validated and agent-ready. The Bullhorn Resume Parsing API converts uploaded CVs and resume documents into structured candidate records inside the Bullhorn ATS, then lets recruiting workflows build out the candidate's education history, work history, primary skills, and attached files. It is scoped to the candidate intake path: parse a resume, create the candidate entity, enrich it with related sub-entities, and attach the original document. The API is part of Bullhorn's broader staffing platform and uses Bullhorn's standard OAuth 2.0 authorization-code flow with a per-corporation REST base URL.
Install Jentic One Beta
Connect the Bullhorn Resume Parsing API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Bullhorn Resume Parsing API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Bullhorn Resume Parsing API.
Parse a PDF, DOC, or DOCX resume into a Bullhorn candidate record via /resume/parseToCandidate
Create a new candidate entity in the Bullhorn ATS with PUT /entity/Candidate
Attach education records to a candidate via /entity/CandidateEducation
Attach work history records to a candidate via /entity/CandidateWorkHistory
Add primary skills to a candidate by skill ID list
Look up the available skill taxonomy via /options/Skill
Upload the original resume file as a candidate attachment
Use Cases
Patterns agents use Bullhorn Resume Parsing API for, with concrete tasks.
★ Automated resume intake
Convert inbound resume files (PDF, DOC, DOCX) into structured Bullhorn candidate records without manual data entry. The /resume/parseToCandidate endpoint extracts contact details, experience, and education in one call, then the candidate, work history, and education entities are persisted in the ATS. Suitable for high-volume staffing agencies processing hundreds of resumes per day.
Parse a resume PDF via POST /resume/parseToCandidate, create the returned candidate with PUT /entity/Candidate, then attach the original file with PUT /file/Candidate/{candidateId}/raw.
Candidate enrichment after parsing
After a candidate is created from a parsed resume, attach structured education and work history sub-entities and assign primary skills from the Bullhorn taxonomy. This produces a fully populated candidate profile that recruiters can search by skill, school, or employer. Typical enrichment runs in under a minute per candidate when the resume contains complete history sections.
For candidate 12345, PUT /entity/CandidateEducation for each school, PUT /entity/CandidateWorkHistory for each role, and PUT /entity/Candidate/12345/primarySkills/{skillIds} with the matched skill IDs.
Resume file management
Maintain a clean audit trail by storing the original resume document alongside the parsed candidate record. The file attachment endpoint accepts the raw binary, and the candidate files listing endpoint lets recruiters confirm what artifacts have been preserved. This satisfies common compliance and audit requirements in staffing operations.
Attach the source resume to candidate 12345 via PUT /file/Candidate/12345/raw, then GET /entityFiles/Candidate/12345 to confirm the file appears in the candidate's file list.
AI agent recruiting assistant via Jentic
An AI recruiting assistant accepts an emailed resume, parses it, creates a Bullhorn candidate, and confirms the import to the recruiter — all without the agent handling raw OAuth tokens. Jentic stores the Bullhorn refresh token and issues scoped access for each call, so the agent only ever sees the structured response from each operation.
Search Jentic for 'parse a resume into Bullhorn', load the parseToCandidate operation schema, then execute it with the resume bytes and report the new candidate ID back to the recruiter.
Key Endpoints
9 endpoints — jentic publishes the only available openapi specification for bullhorn resume parsing api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/resume/parseToCandidate
Parse a resume document into candidate data
PUT
/entity/Candidate
Create a candidate entity
GET
/entity/Candidate/{candidateId}
Retrieve a candidate
PUT
/entity/CandidateEducation
Create a candidate education record
PUT
/entity/CandidateWorkHistory
Create a candidate work history record
PUT
/entity/Candidate/{candidateId}/primarySkills/{skillIds}
Add primary skills to a candidate
PUT
/file/Candidate/{candidateId}/raw
Attach a resume file to a candidate
GET
/entityFiles/Candidate/{candidateId}
List files attached to a candidate
POST
/resume/parseToCandidate
Parse a resume document into candidate data
PUT
/entity/Candidate
Create a candidate entity
GET
/entity/Candidate/{candidateId}
Retrieve a candidate
PUT
/entity/CandidateEducation
Create a candidate education record
PUT
/entity/CandidateWorkHistory
Create a candidate work history record
PUT
/entity/Candidate/{candidateId}/primarySkills/{skillIds}
Add primary skills to a candidate
PUT
/file/Candidate/{candidateId}/raw
Attach a resume file to a candidate
GET
/entityFiles/Candidate/{candidateId}
List files attached to a candidate
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
Bullhorn OAuth refresh tokens and the corpToken stay encrypted in the Jentic vault. Agents receive scoped access tokens only for the operation they are running, so the long-lived secret never enters the agent's context.
Intent-based discovery
Agents search Jentic by intent (e.g., 'parse a resume into Bullhorn') and the matching parseToCandidate operation is returned with its full request schema, so the agent calls the right endpoint without reading Bullhorn docs.
Time to first call
Direct Bullhorn integration: 3-5 days for OAuth setup, corpToken handling, and candidate sub-entity wiring. Through Jentic: under 1 hour — search, load schema, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Bullhorn Resume Parsing API through Jentic.
Why is there no official OpenAPI spec for Bullhorn Resume Parsing API?
Bullhorn does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Bullhorn Resume Parsing API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Bullhorn Resume Parsing API use?
It uses OAuth 2.0 authorization-code flow against https://auth.bullhornstaffing.com/oauth/authorize and /oauth/token. Each request also includes a per-corporation REST base URL that contains your corpToken. Through Jentic, refresh tokens stay in the vault and the agent only receives short-lived access tokens scoped to the call it is making.
Can I parse a PDF resume directly with the Bullhorn Resume Parsing API?
Yes. POST /resume/parseToCandidate accepts the resume binary and returns a candidate object with parsed fields populated. You can then persist that object with PUT /entity/Candidate and attach the original file with PUT /file/Candidate/{candidateId}/raw.
How do I add work history and education to a Bullhorn candidate after parsing?
Use PUT /entity/CandidateWorkHistory with the candidate ID and role data for each previous job, and PUT /entity/CandidateEducation for each school. These calls are independent and can be parallelised to speed up bulk imports.
What are the rate limits for the Bullhorn Resume Parsing API?
The OpenAPI spec does not declare rate limits. Bullhorn enforces per-corporation REST throttles documented in the Bullhorn developer portal — design batch resume imports with retry on 429 responses and back off when the platform signals contention.
How do I parse a resume with Bullhorn through Jentic?
Install the Jentic SDK with `pip install jentic`, then search for 'parse a resume into Bullhorn'. Jentic returns the parseToCandidate operation, you load its schema, and execute with the resume bytes — credentials are pulled from the Jentic vault automatically.
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