One way to solve this, in a large scale manner, would by using PD3O - A New Primal Dual Algorithm for Minimizing the Sum of Three Functions with a Linear Operator.
This is a 3 operators primal dual split method:
$$ \arg \min_{\boldsymbol{x}} \underbrace{\frac{1}{2} {\left\| \boldsymbol{A} \boldsymbol{x} - \boldsymbol{b} \right\|}_{2}^{2} }_{ f \left( \boldsymbol{x} \right) } + \underbrace{ {\lambda}_{1} {\left\| \boldsymbol{x} \right\|}_{2} }_{g \left( \boldsymbol{x} \right)} + \underbrace{
{\lambda}_{2} {\left\| \boldsymbol{x} \right\|}_{2}^{2} }_{ h \left( \boldsymbol{P} \boldsymbol{x} \right) } $$
The method, in general, requires the following:
- $ {\nabla}_{\boldsymbol{x}} f \left( \boldsymbol{x} \right) = \boldsymbol{A}^{T} \left( \boldsymbol{A} \boldsymbol{x} - \boldsymbol{b} \right) $.
- $ \operatorname{Prox}_{\lambda g \left( \cdot \right)} \left( \boldsymbol{y} \right) = \boldsymbol{y} \left( 1 - \frac{\lambda}{\max \left( {\left\| \boldsymbol{y} \right\|}_{2} , \lambda \right)} \right) $.
See Closed Form Solution of $ \arg \min_{x} {\left\| x - y \right\|}_{2}^{2} + \lambda {\left\|x \right\|}_{2} $ - Tikhonov Regularized Least Squares.
- $ \operatorname{Prox}_{\lambda h \left( \cdot \right)} \left( \boldsymbol{y} \right) = {\left( \boldsymbol{I} + \lambda \boldsymbol{I} \right)}^{-1} \boldsymbol{y} $.
Due to the fact $ \boldsymbol{P} = \boldsymbol{I} $.
This is basically a constant scaling of each element of $ \boldsymbol{y} $.
In the specific form of the problem above it will require not matrix decomposition or inversion.

It is also pretty fast to converge (Case of $ \boldsymbol{A} \in \mathbb{R}^{500 \times 400} $) for the case above while the run time is also quite fast (Can be farther optimized).
The Julia code is available at my StackExchange Mathematics Q3800282 GitHub Repository (Look at the Mathematics\Q3800282 folder).