diff --git a/doc/releases/changelog-dev.md b/doc/releases/changelog-dev.md
index bd94ad01217..3b07fae6cfa 100644
--- a/doc/releases/changelog-dev.md
+++ b/doc/releases/changelog-dev.md
@@ -38,6 +38,13 @@
   
 <h3>Breaking changes</h3>
 
+<h3>Bug fixes</h3>
+
+* Fixed a bug where `QNGOptimizer` did not work with operators
+  whose generator was a Hamiltonian.
+  [(#2524)](https://github.com/PennyLaneAI/pennylane/pull/2524)
+
+
 <h3>Deprecations</h3>
 
 <h3>Documentation</h3>
@@ -46,4 +53,5 @@
 
 This release contains contributions from (in alphabetical order):
 
-Utkarsh Azad, Christian Gogolin, Christina Lee
+Guillermo Alonso-Linaje, Utkarsh Azad, Christian Gogolin, Christina Lee
+
diff --git a/pennylane/operation.py b/pennylane/operation.py
index 07fb7d9a103..a26fc71dfc4 100644
--- a/pennylane/operation.py
+++ b/pennylane/operation.py
@@ -2478,3 +2478,19 @@ def defines_diagonalizing_gates(obj):
         except DiagGatesUndefinedError:
             return False
         return True
+
+
+@qml.BooleanFn
+def gen_is_multi_term_hamiltonian(obj):
+    """Returns ``True`` if an operator has a generator defined and it is a Hamiltonian
+    with more than one term."""
+
+    try:
+        o = obj.generator()
+    except (AttributeError, OperatorPropertyUndefined, GeneratorUndefinedError):
+        return False
+
+    if isinstance(o, qml.Hamiltonian):
+        if len(o.coeffs) > 1:
+            return True
+    return False
diff --git a/pennylane/transforms/tape_expand.py b/pennylane/transforms/tape_expand.py
index e3444d3c6f6..a50bd8afa51 100644
--- a/pennylane/transforms/tape_expand.py
+++ b/pennylane/transforms/tape_expand.py
@@ -19,6 +19,7 @@
 import pennylane as qml
 from pennylane.operation import (
     has_gen,
+    gen_is_multi_term_hamiltonian,
     has_grad_method,
     has_nopar,
     has_unitary_gen,
@@ -136,7 +137,7 @@ def expand_fn(tape, depth=depth, **kwargs):
 
 expand_multipar = create_expand_fn(
     depth=10,
-    stop_at=not_tape | is_measurement | has_nopar | has_gen,
+    stop_at=not_tape | is_measurement | has_nopar | (has_gen & ~gen_is_multi_term_hamiltonian),
     docstring=_expand_multipar_doc,
 )
 
@@ -159,7 +160,11 @@ def expand_fn(tape, depth=depth, **kwargs):
 
 expand_trainable_multipar = create_expand_fn(
     depth=10,
-    stop_at=not_tape | is_measurement | has_nopar | (~is_trainable) | has_gen,
+    stop_at=not_tape
+    | is_measurement
+    | has_nopar
+    | (~is_trainable)
+    | (has_gen & ~gen_is_multi_term_hamiltonian),
     docstring=_expand_trainable_multipar_doc,
 )
 
diff --git a/tests/optimize/test_qng.py b/tests/optimize/test_qng.py
index e4cc6c1fed8..8363191e3a7 100644
--- a/tests/optimize/test_qng.py
+++ b/tests/optimize/test_qng.py
@@ -72,6 +72,31 @@ def circuit(params):
         assert np.allclose(step1, expected_step)
         assert np.allclose(step2, expected_step)
 
+    def test_step_and_cost_autograd_with_gen_hamiltonian(self, tol):
+        """Test that the correct cost and step is returned via the
+        step_and_cost method for the QNG optimizer when the generator
+        of an operator is a Hamiltonian"""
+
+        dev = qml.device("default.qubit", wires=4)
+
+        @qml.qnode(dev)
+        def circuit(params):
+            qml.DoubleExcitation(params[0], wires=[0, 1, 2, 3])
+            qml.RY(params[1], wires=0)
+            return qml.expval(qml.PauliZ(0))
+
+        var = np.array([0.011, 0.012])
+        opt = qml.QNGOptimizer(stepsize=0.01)
+
+        step1, res = opt.step_and_cost(circuit, var)
+        step2 = opt.step(circuit, var)
+
+        expected = circuit(var)
+        expected_step = var - opt.stepsize * 4 * qml.grad(circuit)(var)
+        assert np.all(res == expected)
+        assert np.allclose(step1, expected_step)
+        assert np.allclose(step2, expected_step)
+
     def test_step_and_cost_with_grad_fn_grouped_input(self, tol):
         """Test that the correct cost and update is returned via the step_and_cost
         method for the QNG optimizer when providing an explicit grad_fn.
diff --git a/tests/test_operation.py b/tests/test_operation.py
index 77810ffde94..ba35455a1bc 100644
--- a/tests/test_operation.py
+++ b/tests/test_operation.py
@@ -1531,6 +1531,7 @@ class DummyOp(qml.operation.CVOperation):
 
 
 class TestCriteria:
+    doubleExcitation = qml.DoubleExcitation(0.1, wires=[0, 1, 2, 3])
     rx = qml.RX(qml.numpy.array(0.3, requires_grad=True), wires=1)
     stiff_rx = qml.RX(0.3, wires=1)
     cnot = qml.CNOT(wires=[1, 0])
@@ -1555,6 +1556,13 @@ def test_has_grad_method(self):
         assert qml.operation.has_grad_method(self.rot)
         assert not qml.operation.has_grad_method(self.cnot)
 
+    def test_gen_is_multi_term_hamiltonian(self):
+        """Test gen_is_multi_term_hamiltonian criterion."""
+        assert qml.operation.gen_is_multi_term_hamiltonian(self.doubleExcitation)
+        assert not qml.operation.gen_is_multi_term_hamiltonian(self.cnot)
+        assert not qml.operation.gen_is_multi_term_hamiltonian(self.rot)
+        assert not qml.operation.gen_is_multi_term_hamiltonian(self.exp)
+
     def test_has_multipar(self):
         """Test has_multipar criterion."""
         assert not qml.operation.has_multipar(self.rx)