ai-platform: No eval folder or export folder in outputs when running TensorFlow 2.1 training job using Estimators

The Problem

My code works locally, but I am not able to get any evaluation data or exports from my TensorFlow estimator when submitting online training jobs after having upgraded to TensorFlow 2.1. Here's the bulk of my code:

def build_estimator(model_dir, config):

    return tf.estimator.LinearClassifier(
        feature_columns=feature_columns,
        n_classes=2,
        optimizer=tf.keras.optimizers.Ftrl(
            learning_rate=args.learning_rate,
            l1_regularization_strength=args.l1_strength
        ),
        model_dir=model_dir,
        config=config
    )

run_config = tf.estimator.RunConfig(save_checkpoints_steps=100,
                                    save_summary_steps=100)  
...

estimator = build_estimator(model_dir=args.job_dir, config=run_config)

...

def serving_input_fn():
    inputs = {
        'feature1': tf.compat.v1.placeholder(shape=None, dtype=tf.string),
        'feature2': tf.compat.v1.placeholder(shape=None, dtype=tf.string),
        'feature3': tf.compat.v1.placeholder(shape=None, dtype=tf.string),
        ...
    }

    split_features = {}

    for feature in inputs:
        split_features[feature] = tf.strings.split(inputs[feature], "||").to_sparse()

    return tf.estimator.export.ServingInputReceiver(features=split_features, receiver_tensors=inputs)

exporter_cls = tf.estimator.LatestExporter('predict', serving_input_fn)

eval_spec = tf.estimator.EvalSpec(
    input_fn=lambda: input_eval_fn(args.test_dir),
    exporters=[exporter_cls],
    start_delay_secs=10,
    throttle_secs=0)

tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)

If I run this with local gcloud command it works fine, I get my /eval and /export folders:

gcloud ai-platform local train \
--package-path trainer \
--module-name trainer.task \
-- \
--train-dir $TRAIN_DATA \
--test-dir $TEST_DATA \
--training-steps $TRAINING_STEPS \
--job-dir $OUTPUT

But when I try to run it in the cloud, i do not get my /eval /export folders. This only started happening when upgrading to 2.1. Previously everything worked fine in 1.14.

    gcloud ai-platform jobs submit training $JOB_NAME \
    --job-dir $OUTPUT_PATH \
    --staging-bucket gs://$STAGING_BUCKET_NAME \
    --runtime-version 2.1 \
    --python-version 3.7 \
    --package-path trainer/ \
    --module-name trainer.task \
    --region $REGION \
    --config config.yaml \
    -- \
    --train-dir $TRAIN_DATA \
    --test-dir $TEST_DATA \

What I've tried

Instead of relying on the EvalSpec to export my model, I also tried using tf.estimator.export_saved_model. While this works both locally and online, i'd like to continue using the EvalSpec with train_and_evaluate if possible, because I can pass in different export methods like BestExporter, LastExporter, etc.

My main question is...

Am I incorrectly exporting my model in TensorFlow 2.1, or is this a bug that is happening on the platform with the new version?