diff --git a/src/axolotl/core/trainer_builder.py b/src/axolotl/core/trainer_builder.py
index 878dd176a..863b065e6 100755
--- a/src/axolotl/core/trainer_builder.py
+++ b/src/axolotl/core/trainer_builder.py
@@ -1195,7 +1195,9 @@ class HFRLTrainerBuilder(TrainerBuilderBase):
 
         if self.cfg.plugins:
             plugin_manager = PluginManager.get_instance()
-            trainer_cls = plugin_manager.get_trainer_cls(self.cfg)
+            temp_trainer_cls = plugin_manager.get_trainer_cls(self.cfg)
+            if temp_trainer_cls is not None:
+                trainer_cls = temp_trainer_cls
 
         sig = inspect.signature(trainer_cls)
         if "tokenizer" in sig.parameters.keys():
diff --git a/tests/core/test_trainer_builder.py b/tests/core/test_trainer_builder.py
index fbfd7a87c..d1ad273ea 100644
--- a/tests/core/test_trainer_builder.py
+++ b/tests/core/test_trainer_builder.py
@@ -8,6 +8,7 @@ from axolotl.core.trainer_builder import HFRLTrainerBuilder
 from axolotl.utils.config import normalize_config
 from axolotl.utils.dict import DictDefault
 from axolotl.utils.models import load_model, load_tokenizer
+from axolotl.utils.schemas.enums import RLType
 
 
 @pytest.fixture(name="cfg")
@@ -65,3 +66,27 @@ class TestHFRLTrainerBuilder:
         assert training_arguments.adam_epsilon == 0.00001
         assert training_arguments.dataloader_num_workers == 1
         assert training_arguments.dataloader_pin_memory is True
+
+
+class TestTrainerClsPlugin:
+    """
+    TestCase class for trainer builder with plugin
+    """
+
+    def test_trainer_cls_is_not_none_with_plugin(self, cfg, model, tokenizer):
+        """
+        Test that the trainer cls is not none with plugin
+
+        Fixes #2693
+        """
+        cfg.plugins = ["axolotl.integrations.liger.LigerPlugin"]
+        cfg.rl = RLType.KTO
+
+        # Expected AttributeError as we don't pass regular model configs to RL trainer builder
+        # If it throws `TypeError: None is not a callable object`, trainer_cls could be None
+        with pytest.raises(
+            AttributeError, match=r".*'tuple' object has no attribute 'config'.*"
+        ):
+            builder = HFRLTrainerBuilder(cfg, model, tokenizer)
+
+            builder.build(100)