We present the design, development, and experimental characterization of an active electrode (AE) IC for wearable ambulatory EEG recording. The proposed architecture features in-AE double common-mode (CM) rejection, making the recording's CMRR independent of typically-significant AE-to-AE gain variations. Thanks to being DC coupled and needless of chopper stabilization for flicker noise suppression, the architecture yields a super-T Ω input impedance. Such a large input impedance makes the AE's CMRR practically immune to electrode-skin interface impedance variations across different recording channels, a critical feature for dry-electrode ambulatory systems. Signal quantization and serialization are also performed in-AE, which enables a distributed system in which all AEs use a single data bus for data/command communication to the backend module, thus significantly improving the system's scalability. Additionally, the presented AE hosts auxiliary modules for (i) detection of an unstable electrode-skin connection through continuous interface impedance monitoring, (ii) dynamic measurement and adjustment of input DC level, and (iii) a CM feedback loop for further CMRR enhancement. The article also presents the development of printed (extrusion) tattoo electrodes and their experimental characterization results with the proposed AE architecture. Besides bio-compatibility, low-cost, pattern flexibility, and quick fabrication process, the printed electrodes offer a very stable electrode-skin connection, conform to scalp shape, and exhibit consistent performance under various bending curvatures. Analog circuit blocks of the presented AE architecture are designed and fabricated using a standard 180 nm CMOS technology, and the [Formula: see text] IC is integrated with off-chip low-power digital modules on a PCB to form the AE. Our measurement results show a CMRR of 82.2 dB (at 60 Hz), amplification voltage gain of 52.8 dB, a bandwidth of 0.2-400 Hz, ±500 mV input DC offset tolerance, An input impedance [Formula: see text], and 0.67 μV RMS integrated input referred noise (0.5-100 Hz), while consuming 17.5 μW per channel. All auxiliary modules are tested experimentally, and the entire system is validated in-vivo, for both ECG and EEG recording.