Bullhorn Resume Parsing API

Name: Bullhorn Resume Parsing API
Brand: Bullhorn Resume Parsing API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentHR recruitingRecruiting Atsoauth29 EndpointsREST

For Agents

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.

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 | sh

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 instance

Jentic 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

GET STARTED

Start building with Bullhorn Resume Parsing API

Explore with Jentic

View OpenAPI Document

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.

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

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your Bullhorn OAuth refresh token and corpToken are stored once, encrypted, by your own Jentic One instance, and only a scoped access token is injected at execution time. The long-lived secrets never enter the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'parse a resume into Bullhorn' or 'attach a candidate work history', and Jentic returns the matching Bullhorn operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

Time to first call

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 with Jentic One, the self-hosted execution layer.

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 your Jentic One instance automatically.

Can I limit what my agent is allowed to do with the Bullhorn Resume Parsing API?

Yes. Because you run Jentic One yourself, your own rules decide which Bullhorn operations and credentials the agent may use, so you can allow it to parse a resume with POST /resume/parseToCandidate and create a record with PUT /entity/Candidate while blocking everything else. Since Bullhorn puts the candidate id in the URL path, a rule can pin the agent to a single candidate and let it attach only that person's education, work history, and skills through /entity/CandidateEducation, /entity/CandidateWorkHistory, and the primarySkills path. It cannot reach unrelated entities or attach files unless you add those operations to its allowed set. The refresh token and corpToken stay with your instance, and only a scoped access token is injected when a permitted call runs.