diff --git a/lib/modules/embeddings/jobs/regular/generate_embeddings.rb b/lib/modules/embeddings/jobs/regular/generate_embeddings.rb
index 919b43c6..a76f1ad8 100644
--- a/lib/modules/embeddings/jobs/regular/generate_embeddings.rb
+++ b/lib/modules/embeddings/jobs/regular/generate_embeddings.rb
@@ -13,9 +13,9 @@ module Jobs
 
       strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
       vector_rep =
-        DiscourseAi::Embeddings::VectorRepresentations::Base.find_vector_representation.new
+        DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
 
-      vector_rep.generate_topic_representation_from(topic, strategy)
+      vector_rep.generate_topic_representation_from(topic)
     end
   end
 end
diff --git a/spec/lib/modules/embeddings/jobs/generate_embeddings_spec.rb b/spec/lib/modules/embeddings/jobs/generate_embeddings_spec.rb
new file mode 100644
index 00000000..258161ee
--- /dev/null
+++ b/spec/lib/modules/embeddings/jobs/generate_embeddings_spec.rb
@@ -0,0 +1,39 @@
+# frozen_string_literal: true
+
+require_relative "../../../../support/embeddings_generation_stubs"
+
+RSpec.describe Jobs::GenerateEmbeddings do
+  subject(:job) { described_class.new }
+
+  describe "#execute" do
+    before do
+      SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
+      SiteSetting.ai_embeddings_enabled = true
+      SiteSetting.ai_embeddings_model = "all-mpnet-base-v2"
+    end
+
+    fab!(:topic) { Fabricate(:topic) }
+    fab!(:post) { Fabricate(:post, post_number: 1, topic: topic) }
+
+    let(:truncation) { DiscourseAi::Embeddings::Strategies::Truncation.new }
+    let(:vector_rep) do
+      DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(truncation)
+    end
+
+    it "works" do
+      expected_embedding = [0.0038493] * vector_rep.dimensions
+
+      text =
+        truncation.prepare_text_from(
+          topic,
+          vector_rep.tokenizer,
+          vector_rep.max_sequence_length - 2,
+        )
+      EmbeddingsGenerationStubs.discourse_service(vector_rep.name, text, expected_embedding)
+
+      job.execute(topic_id: topic.id)
+
+      expect(vector_rep.topic_id_from_representation(expected_embedding)).to eq(topic.id)
+    end
+  end
+end