Is there a more efficient algorithm besides Gram-Schmidt that would produce an orthonormal matrix of rank N, with first row equal to [1 1 1 1 1 ... 1] / sqrt(N)?
e.g. for N = 3, the matrix $\begin{align} \mathsf A_3 &= \begin{bmatrix} 1/\sqrt 3 & 1/\sqrt 3 & 1/\sqrt 3 \\ 2/\sqrt 6 & -1/\sqrt 6 & -1/\sqrt 6 \\ 0 & 1/\sqrt 2 & -1/\sqrt 2 \end{bmatrix}\end{align}$ suffices, but I'm not sure how to generalize.
There's a reflection swapping $v=(\sqrt{n},0,\ldots,0)$ with $w=(1,1,\ldots,1)$ which will do what you want. It will fix $v+w$ and all vectors orthogonal to $v$ and $w$. It will negate $v-w$. It will be a symmetric matrix; its first row and column is all $1/\sqrt{n}$. The remaining entries $a_{i,j}$ for $i$, $j\ge2$ will depend only on whether $i=j$ or not. This should be enough information to reconstruct it.