Feature Request: Add `pgvector` extension

**Describe the Feature Request**
Add the pgvector extension to CircleCI's cimg-postgres Docker image to support efficient storage and search of vector data from machine learning models, aligning with industry trends towards ML integration. E.g. [Amazon RDS installs the extension in their Postgres datbases](https://aws.amazon.com/about-aws/whats-new/2023/05/amazon-rds-postgresql-pgvector-ml-model-integration/).

**Is your feature request related to a particular problem?**

Yes, the absence of pgvector necessitates custom Docker images, slowing down CI/CD pipelines and introducing potential inconsistencies.

**How will this feature request benefit CircleCI jobs using this image?**

Incorporating pgvector will streamline workflows for ML projects, reduce setup times, and offer a consistent environment, making CircleCI more attractive to developers working with vector embeddings.

**Describe the solution you would like to see**

The pgvector extension installed by default in the cimg-postgres Docker image, compatible with its PostgreSQL versions and easily enabled via `CREATE EXTENSION vector;`

**Describe alternatives you have considered**

Manually installing pgvector or creating a custom Docker image. The former isn't possible and the latter is cumbersome and increases complexity.

Start by inspecting the cimg-postgres Docker image build definitions and the PostgreSQL version matrix. Check how extensions are packaged and enabled, then verify that `CREATE EXTENSION vector;` works for the supported PostgreSQL versions. Done means the image includes pgvector without requiring a custom image.

Written by the indexing model from the issue text.