Complex geometry, variable macrostructure, anisotropy, distributed defects, surface roughness, and residual stresses of additively manufactured (AM) components challenge nondestructive evaluation processes developed and validated for conventional manufacturing. Electromagnetic and eddy current (EC) technologies were identified as promising for in-process, real-time monitoring, and post-process examination of AM components. Powder and solid specimens were prepared for electromagnetic property measurements and technique development and optimization. The post-process specimens were fabricated with roughness representative of surface conditions during fabrication inside the AM machine. Artificial and natural discontinuities were fabricated with the electrical discharge machining process and by varying the laser fusion parameters. Extensive computed modeling was conducted to develop an optimized array EC (AEC) sensor and technique for AM real-time monitoring. The AEC sensor could withstand temperatures up to 100ºC. Computational modeling was conducted to investigate the likelihood of metal powder disturbance by the EC sensor electromagnetic field. A real-time data acquisition system was assembled and integrated with an open-architecture laser powder bed fusion (L-PBF) test bed. The EC system performance for real-time monitoring of the L-PBF process was demonstrated through layer-by-layer testing of Inconel 625 coupons, with AM built discontinuities and lack of fusion. The L-PBF process was representative of a typical AM process used for super alloys and steels with preheat of substrate plate and AM test specimens to 100ºC. Existing AEC equipment and techniques were used for post-process examination of AM solid specimens at room temperatures. The AEC technology demonstrated excellent sensitivity to seeded and natural surface and near-surface subsurface discontinuities and surface topography during real-time monitoring and post-processing. Electromagnetic and EC techniques were demonstrated to examine powder before fabrication. The application of modeling tools reduced developmental time and improved efficiency. Further research and development was recommended to improve data acquisition process and transition AEC monitoring technology to other AM processes.