I'm looking for behavior similiar to that of LCGs, (i.e. input and output sizes are same). Full cycle of $2^{32}$ different inputs generates full cycle of $2^{32}$ different outputs, distribution of which depends on large key. Obviously combined LCGs (with generated parameters based on the perturb seed key) seem trivially invertible through modular inverse, but you get the idea.
The hash has to accept small input and produce never-colliding equal sized output, and is keyed with large 'salt'/'nonce' key, to make precomputing generic table of all $2^{32}$ hashes for trivial inversion infeasible. The hash has to remain one way when 'seed' key and output is known (ie input should be difficult to compute out of those, short of bruteforcing 2^31 inputs for each particular seed+output and meeting in the middle for birthday).
This exotic requirement sets it apart from classical bijective trapdoor functions (RSA, MQ et al), as the output has to be much smaller than some input parameters (ie the "salt" seed).
Is this even feasible? It does not appear to be with traditional ARX/feistel, however I suspect there are still useable trapdoors in number theory - for example FSB and SWIFFTX. However I'm not sure if those can be adapted to the requirement above.
I'm OK with security parameter well below nbits/2, as long it is still reasonably difficult to invert algebraically.
Bottom line: Albeit related, perfect hash functions are not acceptable answer as there does not seem to be examples of cryptographically secure ones, much less any working as a trapdoor.
Block ciphers such as RC6 or AES rounds show some promise (by using the 'decrypt' part as our hash), but naive implementation seems to be reversible by running the rounds backwards (remember, the cipher key, our "seed" sbox which introduces non-linearity in those is publicly known, whereas the tiny "plaintext" is what is to be protected).
I presume block ciphers which break linearity through heavy input data dependency might work, however I have no idea what candidates I should be looking for.