The Giant Gartersnake (Thamnophis gigas) is a low density visually evasive species with a low detection probability based on standard field survey methods (e.g., traps, visual census). Habitat loss has resulted in extirpations or serious declines for T. gigas populations throughout the southern two thirds of its historic range. Uncertainty regarding its current distribution and occupancy present management challenges for the species. Enhancing survey sensitivity through development of environmental DNA sampling (eDNA) methods would improve compliance monitoring under the Endangered Species Act, recovery planning for T. gigas, and evaluation of California's Central Valley tule marsh habitat on which this species depends. To address these needs, we designed and validated diagnostic quantitative Polymerase Chain Reaction (qPCR) assays for identifying portions of the Cytochrome B (CytB) and the Nicotinamide adenine dinucleotide (NADH) dehydrogenase subunit 4 (ND4) genes of the T. gigas mitochondrial genome. The designed ND4 qPCR assay was not specific to T. gigas DNA and amplified DNA from a closely related and spatially co-occurring Thamnophis species (T.s. fitchi). The CytB T. gigas qPCR assay proved specific to a species level with a sensitivity that reliably detected T. gigas DNA at a concentration of 2.0x10-5 ng μL-1. To assess detection range, coordinated field sampling was conducted at aquatic sites with an observed and documented population of T. gigas. The T. gigas qPCR assay reliably detected DNA from samples taken 300m downstream from the known source. We then used environmental eDNA sampling and qPCR analysis to augment unsuccessful trap surveys in the southern range of T. gigas and detected DNA in 28 of the 52 locations sampled, confirming that T. gigas was still present at some sites where physical trapping failed to identify presence. QPCR-based DNA detection coupled with eDNA sampling methods provides an effective means to obtain critical population metrics from this otherwise cryptic, federally protected and hard to study organism, offering great promise for elucidating patterns of occupancy with greater efficiency and at far less cost than trapping methods, particularly where detection probabilities are low.