diff --git a/haystack/nodes/answer_generator/openai.py b/haystack/nodes/answer_generator/openai.py
index 003812a91..6cad70994 100644
--- a/haystack/nodes/answer_generator/openai.py
+++ b/haystack/nodes/answer_generator/openai.py
@@ -186,7 +186,9 @@ class OpenAIAnswerGenerator(BaseGenerator):
             logger.debug("Using GPT2TokenizerFast")
             self._hf_tokenizer: PreTrainedTokenizerFast = GPT2TokenizerFast.from_pretrained(tokenizer)
 
-    @retry_with_exponential_backoff(backoff_in_seconds=OPENAI_BACKOFF, max_retries=OPENAI_MAX_RETRIES)
+    @retry_with_exponential_backoff(
+        backoff_in_seconds=OPENAI_BACKOFF, max_retries=OPENAI_MAX_RETRIES, errors=(OpenAIRateLimitError, OpenAIError)
+    )
     def predict(
         self,
         query: str,
diff --git a/haystack/nodes/prompt/prompt_node.py b/haystack/nodes/prompt/prompt_node.py
index 3cff64f1f..8964585fa 100644
--- a/haystack/nodes/prompt/prompt_node.py
+++ b/haystack/nodes/prompt/prompt_node.py
@@ -20,7 +20,11 @@ from transformers import (
 from transformers.models.auto.modeling_auto import MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES
 
 from haystack import MultiLabel
-from haystack.environment import HAYSTACK_REMOTE_API_BACKOFF_SEC, HAYSTACK_REMOTE_API_MAX_RETRIES
+from haystack.environment import (
+    HAYSTACK_REMOTE_API_BACKOFF_SEC,
+    HAYSTACK_REMOTE_API_MAX_RETRIES,
+    HAYSTACK_REMOTE_API_TIMEOUT_SEC,
+)
 from haystack.errors import OpenAIError, OpenAIRateLimitError
 from haystack.modeling.utils import initialize_device_settings
 from haystack.nodes.base import BaseComponent
@@ -435,8 +439,9 @@ class OpenAIInvocationLayer(PromptModelInvocationLayer):
         }
 
     @retry_with_exponential_backoff(
-        backoff_in_seconds=int(os.environ.get(HAYSTACK_REMOTE_API_BACKOFF_SEC, 5)),
+        backoff_in_seconds=float(os.environ.get(HAYSTACK_REMOTE_API_BACKOFF_SEC, 5)),
         max_retries=int(os.environ.get(HAYSTACK_REMOTE_API_MAX_RETRIES, 5)),
+        errors=(OpenAIRateLimitError, OpenAIError),
     )
     def invoke(self, *args, **kwargs):
         """
@@ -478,7 +483,13 @@ class OpenAIInvocationLayer(PromptModelInvocationLayer):
             "logit_bias": kwargs_with_defaults.get("logit_bias", {}),
         }
         headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}
-        response = requests.request("POST", self.url, headers=headers, data=json.dumps(payload), timeout=30)
+        response = requests.request(
+            "POST",
+            self.url,
+            headers=headers,
+            data=json.dumps(payload),
+            timeout=float(os.environ.get(HAYSTACK_REMOTE_API_TIMEOUT_SEC, 30)),
+        )
         res = json.loads(response.text)
 
         if response.status_code != 200:
diff --git a/haystack/nodes/retriever/_openai_encoder.py b/haystack/nodes/retriever/_openai_encoder.py
index 09134898a..4ba2f0478 100644
--- a/haystack/nodes/retriever/_openai_encoder.py
+++ b/haystack/nodes/retriever/_openai_encoder.py
@@ -104,7 +104,9 @@ class _OpenAIEmbeddingEncoder(_BaseEmbeddingEncoder):
 
         return decoded_string
 
-    @retry_with_exponential_backoff(backoff_in_seconds=OPENAI_BACKOFF, max_retries=OPENAI_MAX_RETRIES)
+    @retry_with_exponential_backoff(
+        backoff_in_seconds=OPENAI_BACKOFF, max_retries=OPENAI_MAX_RETRIES, errors=(OpenAIRateLimitError, OpenAIError)
+    )
     def embed(self, model: str, text: List[str]) -> np.ndarray:
         payload = {"model": model, "input": text}
         headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}