NP-complete is defined with respect to Turing machines, not circuits.
NP-complete specified in terms of polynomial-time algorithms, where polynomial-time algorithms are formalized as Turing machines whose worst-case running time is polynomial. The Tseytin transform doesn't apply directly to Turing machines.
You can try to define an analogue of NP, but for circuits instead of Turing machines. Unfortunately, this runs into some technical problems. In particular, a circuit can only handle a fixed-size input, which means there is no notion of asymptotic running time for a circuit. In contrast, a Turing machine can handle arbitrary-size inputs, and thus we can talk about asymptotic running time (such as polynomial-time). One can try to address this with a family of circuits, but this introduces its own technical challenges. The end result is that we end up with a different complexity class, NP/poly. The question of whether P =? NP is a question about algorithms/Turing machines. There is an analogous questions for circuit complexity classes, namely, P/poly =? NP/poly, but at a technical/mathematical level, it is a different question that might possibly have a different answer.
You can think of the Cook-Levin theorem as like an analogue of the Tseytin transform. The Tseytin transform converts a circuit to a SAT instance. The Cook-Levin theorem converts a Turing machine to a SAT instance. Boolean circuits are "closer to" (more "similar to") boolean formulas than Turing machines are, and consequently the Tseytin transform looks simpler than the Cook-Levin theorem.
To learn more, see https://en.wikipedia.org/wiki/Advice_(complexity), https://en.wikipedia.org/wiki/NP/poly, https://en.wikipedia.org/wiki/P/poly, https://en.wikipedia.org/wiki/Circuit_complexity.