Jobs

Search never returns postings. It returns encrypted string job IDs, and you pass up to 100 of them to the detail route to read the records. There is no one-shot endpoint, so plan for two calls.

# 1. Search. Returns encrypted IDs, never postings.
curl -X POST "https://mira-api.metix.ai/v1/jobs/query" \
  -H "Authorization: Bearer $METIX_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "where": {"all": [
      {"field": "title", "match": "machine learning platform"},
      {"field": "country_iso_2", "eq": "US"},
      {"field": "posted", "gte": "now-30d"},
      {"any": [
        {"field": "seniority", "eq": "Mid-Senior level"},
        {"field": "seniority", "eq": "Director"}
      ]}
    ]},
    "size": 25
  }'

# 2. Read the postings, up to 100 IDs per call.
curl -X POST "https://mira-api.metix.ai/entity/v1/jobs/detail-by-id" \
  -H "Authorization: Bearer $METIX_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "job_ids": ["Jb71xKcAoP", "Jb0mQ4ZtRe"],
    "_source": ["id", "title", "company_name", "location", "seniority", "posted"]
  }'

• Measure hiring demand by role, function, seniority, company, or location.
• Find who is hiring for a capability, then pivot to the companies and people behind it.
• Filter by salary band or posting date to separate live demand from stale listings.

• One operator per leaf. A salary band is an all of two leaves, not gte and lte in one node.
• A field name that is not in this dataset's list is refused, so a typo is visible rather than returning a record without it. The three datasets do not share one vocabulary.
• Search returns at most 10,000 IDs per page and 100 when size is omitted; detail accepts at most 100 IDs per request.
• Jobs declare no scope nodes. One document is one posting, so there is nothing to group.
• The response carries IDs and a cursor, not a match count. Page until next is absent if you need the size of a set.
• The index holds daily active postings. A posting closed since your search can come back in not_found.

These are the only names a leaf may put in field. The grammar around them, including composition, one operator per leaf, and relative dates, is on the Query Spec page. What a response may contain is a separate, wider list: a field can be returnable without being queryable.

{
  "where": {
    "all": [
      {
        "field": "title",
        "match": "backend engineer"
      },
      {
        "field": "application_active",
        "eq": true
      }
    ]
  }
}

{
  "where": {
    "all": [
      {
        "field": "seniority",
        "eq": "Mid-Senior level"
      }
    ]
  }
}

{
  "where": {
    "all": [
      {
        "field": "country",
        "match": "China"
      },
      {
        "field": "city",
        "match": "Shanghai"
      },
      {
        "field": "regions",
        "match": "Asia"
      }
    ]
  }
}

{
  "where": {
    "all": [
      {
        "field": "application_active",
        "eq": true
      }
    ]
  }
}

{
  "where": {
    "all": [
      {
        "field": "salary_currency",
        "eq": "USD"
      }
    ]
  }
}

{
  "where": {
    "all": [
      {
        "field": "required_months_of_experience",
        "gte": 24
      }
    ]
  }
}

These are matched against the whole stored value, so the spelling and the capitalisation both have to match. Getting either wrong is the one mistake in the grammar that raises no error: the query is valid, it costs nothing, and it returns zero, which reads as an answer about the data rather than about the query.

Successful responses use the public envelope with code, msg, and data.

Search returns IDs, and a next cursor while more pages remain:

{
  "code": 200,
  "msg": "ok",
  "data": {
    "job_ids": ["Jb71xKcAoP", "Jb0mQ4ZtRe"],
    "next": "WzE3MjQwMDAwMDAsIkpiNzF4S2NBb1AiXQ"
  }
}

Detail returns the records, and names the IDs it could not resolve:

{
  "code": 200,
  "msg": "ok",
  "data": {
    "total": 2,
    "found": 1,
    "not_found": ["Jb0mQ4ZtRe"],
    "results": [{
      "id": "Jb71xKcAoP",
      "title": "Machine Learning Platform Engineer",
      "company_name": "Example Corp",
      "location": "San Francisco, CA",
      "seniority": "Mid-Senior level",
      "posted": "2026-08-02"
    }]
  }
}

The record itself is a page of its own: every field it can carry, what each one holds, and a whole one to read.

Common next step: look up the companies doing the hiring.