BUG: TypeError for .at indexer when accessing MultiIndex through date string
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
import numpy as np

np.random.seed(0)

tickers = ['AAPL', 'AMZN', 'GOOG']
timestamps = pd.date_range('2021-08-01', freq='12H', periods=8)

index = pd.MultiIndex.from_product([tickers, timestamps], 
                                    names=['ticker', 'timestamp'])

df = pd.DataFrame(np.random.rand(index.shape[0], 4), 
                  columns=['open', 'high', 'low', 'close'], 
                  index=index)

by_day = df.groupby(['ticker', 
                     pd.Grouper(level='timestamp', freq='D')])

df_daily_open = by_day.head(1)

df_daily_open.at[('AMZN', '2021-08-02'), 'open']

```

#### Problem description

Above code throws a TypeError for the `.at[]` indexer:

```python
TypeError: unsupported operand type(s) for +: 'slice' and 'int'

```

Using `.loc[]` instead, works without any issues and gives the expected result:

```python
>>> df_daily_open.loc[('AMZN', '2021-08-02'), 'open']
ticker  timestamp 
AMZN    2021-08-02    0.437032
Name: open, dtype: float64
```

Using a timestamp instead of a date string works for `.at[]`:

```python
>>> df_daily_open.at[('AMZN', pd.to_datetime('2021-08-02')), 'open']
0.43703195379934145

```

#### Output of ``pd.show_versions()``

<details>


INSTALLED VERSIONS
------------------
commit           : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python           : 3.9.1.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.10.60-1-MANJARO
Version          : #1 SMP PREEMPT Wed Aug 18 08:02:07 UTC 2021
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : C
LOCALE           : None.None

pandas           : 1.3.2
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.2.4
setuptools       : 49.2.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.0.1
IPython          : 7.24.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.0
sqlalchemy       : None
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
