AI Engineer - Data Success

Citian•Washington, DC

About The Position

Citian is a fast-growing, venture-backed SaaS technology company based in Washington, DC, developing software for transportation and infrastructure systems. The AI Engineer - Data Success will support the incorporation of AI into data extraction processes using client datasets. Working alongside Engineering, Data, and Research teams, the role helps build scalable data-ingestion processes and improve data integrity. The position calls for resourcefulness, innovation, process improvement, efficiency, and effective collaboration with cross-functional teams and stakeholders. The engineer will assess AI outputs against real-world infrastructure standards, help improve model performance and tool use, and support computer vision and image-recognition strategies for infrastructure asset extraction. The role also contributes to domain-specific model fine-tuning and evaluation, recommends third-party AI tools and foundation models, and manages the application of AI to QA/QC processes to continuously improve data quality and integrity.

Requirements

Bachelor’s degree in Computer Science, Data Science, or a related field.
At least 3 years of professional experience in data-focused roles and at least 1 year of AI-focused experience, ideally in a product environment.
Understanding of Python and SQL code and ability to retrieve and store data safely through a back end.
Familiarity with RESTful APIs and back-end concepts sufficient to prototype, test, and evaluate integrations.
Experience with cloud services, specifically AWS, and ability to use its features for scalable back-end AI solutions is highly desired; examples include S3 and Lambda Functions.
Exposure to civil engineering, transportation infrastructure, or geospatial data sufficient to critically evaluate AI outputs in these domains and communicate credibly with domain experts.

Nice To Haves

Hands-on implementation experience with RESTful API and back-end integrations.
Experience with computer vision or AI image-recognition applications, including at a prototyping or evaluation level.

Responsibilities

Evaluate whether AI outputs meet real-world infrastructure standards and work with technical data teams accordingly.
Help lead efforts to improve model performance, including enabling models with tool use and other techniques to get the best results from LLMs.
Support AI image-recognition and computer-vision strategies for infrastructure asset data extraction by assessing model approaches, overseeing implementation, and validating outputs against domain benchmarks.
Collaborate with the Research team on domain adaptation, benchmarking, and model evaluation for transportation- and infrastructure-specific models.
Evaluate and recommend third-party AI tools, APIs, and foundation models relevant to Citian’s use cases, balancing build-versus-buy tradeoffs in coordination with Engineering.
Own and manage the application of AI to QA/QC processes, direct strategy, evaluate outputs for domain accuracy, and iterate with the Data team to improve data quality and integrity.